{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"## Bias Variance Tradeoff","metadata":{"id":"uZnF8An8nGyx","papermill":{"duration":0.085661,"end_time":"2022-05-24T07:43:49.934123","exception":false,"start_time":"2022-05-24T07:43:49.848462","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"# 1. Introduction\n\nIt’s important to understand prediction errors (bias and variance) wh. There is a tradeoff between a model’s ability to minimize bias and variance. Gaining a proper understanding of these errors would help us not only to build accurate models but also to avoid the mistake of overfitting and underfitting. If our model is too simple and has very few parameters then it may have high bias and low variance. On the other hand if our model has large number of parameters then it's going to have high variance and low bias.\n","metadata":{"papermill":{"duration":0.079952,"end_time":"2022-05-24T07:43:50.095071","exception":false,"start_time":"2022-05-24T07:43:50.015119","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"![](https://media.geeksforgeeks.org/wp-content/uploads/20200107023418/1_oO0KYF7Z84nePqfsJ9E0WQ.png)","metadata":{}},{"cell_type":"markdown","source":"# 2. Understanding Bias\n### What is **Bias**?\n> Bias is the difference between the average prediction of our model and the correct value which we are trying to predict. Model with high bias pays very little attention to the training data and oversimplifies the model. It always leads to high error on training and test data. - *Seema Singh*\n\n### Bias Definition in Statistics\nIn statistics, bias is a term which defines the tendency of the measurement process. It means that it evaluates the over or underestimation of the value of the population parameter. Let us consider an example, in case you have the rule to evaluate the mean of the population. Hopefully, you might have found an estimation using the rule, which is the true reflection of the population. Now, by using the biased estimator, it is easy to find the difference between the true value and the statistically expected value of the population parameter. \n\n### Why it is so important in Data Science?\nDue to society's culture and history, historical data might be discriminatory against certain minority groups. Cognitive biases are systematic errors in thinking, usually inherited by cultural and personal experiences, that lead to distortions of perceptions when making decisions. And while data might seem objective, data is collected and analyzed by humans, and thus can be biased. Because of this, it's highly important to check assumptions over the data to avoid future algorithmic bias.\n\n##### Sometimes it can be helpful too!\n***The idea of having bias was about model giving importance to some of the features in order to generalize better for the larger dataset with various other attributes. Bias in ML does help us generalize better and make our model less sensitive to some single data point.***\n\n*Information : Wikipedia, bmc.com, Investopedia, towardsdatascience.com*\n\n","metadata":{"id":"ls1Fzsh7oms5","papermill":{"duration":0.07964,"end_time":"2022-05-24T07:43:50.254305","exception":false,"start_time":"2022-05-24T07:43:50.174665","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"![1.png](attachment:83ccc825-c1ab-42f0-a1c4-aa721f310e9d.png)","metadata":{"papermill":{"duration":0.080517,"end_time":"2022-05-24T07:43:50.415564","exception":false,"start_time":"2022-05-24T07:43:50.335047","status":"completed"},"tags":[]},"attachments":{"83ccc825-c1ab-42f0-a1c4-aa721f310e9d.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"# 3. Understanding Variance\n### What is \"Variance\"\n\nVariance is a measurement of the spread between numbers in a data set. In probability theory and statistics, variance is the expectation of the squared deviation of a random variable from its population mean or sample mean. Variance is a measure of dispersion, meaning it is a measure of how far a set of numbers is spread out from their average value.\n\n\n### Variance in terms of DS-ML\n> Variance is the variability of model prediction for a given data point or a value which tells us spread of our data. Model with high variance pays a lot of attention to training data and does not generalize on the data which it hasn’t seen before. As a result, such models perform very well on training data but has high error rates on test data. - *Seema Singh*\n\nAlso, variance refers to the changes in the model when using different portions of the training data set. Simply stated, variance is the variability in the model prediction—how much the ML function can adjust depending on the given data set.\n\n\n## Measuring Variance\nIn statistics, variance measures variability from the average or mean. It is calculated by taking the differences between each number in the data set and the mean, then squaring the differences to make them positive, and finally dividing the sum of the squares by the number of values in the data set. [Learn More](https://en.wikipedia.org/wiki/Variance)\n\nBias and variance are used in supervised machine learning, in which an algorithm learns from training data or a sample data set of known quantities. The correct balance of bias and variance is vital to building machine-learning algorithms that create accurate results from their models.\n*Information : Wikipedia, bmc.com, Investopedia, 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4. Understanding Irreducible error\n\nThis error is out of the control of the machine learning engineer who is building the model. It’s an error caused by noise in the data,\nrandom variations that don’t represent a real pattern in the data, or the influence of variables that are not yet captured as features.\nOne way to reduce this type of error is to identify the variables that have impact on the problem we’re modeling and turn them into\nfeatures.","metadata":{"id":"rhzoPw6urLaP","papermill":{"duration":0.079676,"end_time":"2022-05-24T07:43:50.735273","exception":false,"start_time":"2022-05-24T07:43:50.655597","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"# 5. Mathematical Explanation\n\nLet the variable we are trying to predict as Y and other covariates as X. We assume there is a relationship between the two such that\n\nY=f(X) + e\n\nWhere e is the error term and it’s normally distributed with a mean of 0.\n\nWe will make a model f^(X) of f(X) using linear regression or any other modeling technique.\n\nSo the expected squared error at a point x is\n\n![1_BtpFTBrGaQNE3TvU-0EVSQ.png](attachment:5e00ecf6-b9ab-425f-b5c6-d492ce8d248d.png)\n\nThe Err(x) can be further decomposed as\n\n![1_e7VaoBh5apjaM2p4afkFyg.png](attachment:d39d0a5f-a77d-42f9-be29-a2819ba04125.png)\n\nErr(x) is the sum of Bias², variance and the irreducible error.\n\nIrreducible error is the error that can’t be reduced by creating good models. It is a measure of the amount of noise in our data. Here it is important to understand that no matter how good we make our model, our data will have certain amount of noise or irreducible error that can not be removed.\n\n*credit -*[*Seema Singh*](https://medium.com/@seema.singh)","metadata":{"id":"UTWE8djdpmzv","papermill":{"duration":0.079579,"end_time":"2022-05-24T07:43:50.894932","exception":false,"start_time":"2022-05-24T07:43:50.815353","status":"completed"},"tags":[]},"attachments":{"5e00ecf6-b9ab-425f-b5c6-d492ce8d248d.png":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAASIAAABICAIAAADdxG9pAAAMa0lEQVR42uydXWgbV9rHn77kQoFcyOCLY3hfyIBfqIoLHkNAI9gLj9FFFFKwjAuRcMCrdCFVt7Aru5BV0gtXbiGrpODKXQh2AgmjQoO04CAFGqS9cBkZXEaGgBVoGRkcmAEXJHBAggS0zEi29TGjL0uy5T4/CsUZaT6e8/zPOc/H2OcKhQIgCNJN/gdNgCAoMwRBmSEIgjJDEJQZgqDMEARBmSEIygxBEJQZgqDMEARlhiAIygxBUGYIgjJDToiNxffK+Tgoo006R+KrCutO/SCjzP6w+PjCAT86CNqjczB3Di0rcdO4miH9SfrZZxPXV1Nv0BIoM6RLGnt6Y+IvKZJfZT9aTKDSUGZIVzR23+BPxLgfo9GrvN2KSkOZIZ2GGvfGngfsFwHASP8tknzkoC+c0K28SS7/eWKC/WBo6IMrX0TTKDPk7DBIUcajn8j7lOFk7iMb/WIufY2LxbdTQbv0zyuWz6NZlBmCdBI5zv0rfu+7SBrAOO5yW0H+bjX6GmXWXiTwbM75bSLftO3Dn95Y3sqfBTdSdkSfhV/38yPsROcc95oevHziW+fcM42tX37jnrN2T0hM7CzrukSdV344f15ZYKXMCS5nhc6yH3E3vqad2+3ApcSgg5h9/H4r30lzDsL4ErlCT8hFmzDGNCfVfjPhq6ibVRuZ95mJIyiqPwi+6poa8a4ffVYK2suP0feFrj5yZt3vGDGZzIxjSch1diAqnrrCzPwCQ2Y4sa5PkqsBrRuSuGmwB6VuewJ05ay/rrDKmLIrv1baIx3xmqGeA7VyCRsw/mTrfrDmJsQd2Sv0DPGBagzrSoUfvM2JUS8DAAtaxqgns1xsnpCbkUzlRVYuqzK6ulLrbdtLDBCbLy7m3nb5UZN+BoC943MPA4AjpOu9yt0ybQheOb/moAt+s94JFRGC2R1Ja56xn2WWWVNncaLhKOJjOxDfsWdUxTpkPtbWqqSMMbkV69GKVshEbqrG0JCTyE0C+VpoSWa5hI8GW9X8pZzroU3VmSu0d1ILeC52iyijvuSnAcik7vKiLLDEE9tv6xLzBC5rTCW5nzxE0yxBh2naz+/Vc6R+lRm/oO5jqmfcAwfS3Ca1ZGzF1eg2lrKS44ddoDUk3YEvburcaxktQ+mMsa7M1Oag2VBGe3lXdRbONLHR6gaCf1R5UGXU9zO6ss7xvlGg7wptL5g0EG88p3n1qtlTDDrYv3Lbip6l0E13aPfEZNaNFEh6e11Wtoy06SC1m5d/SaTVMmV2T4JB4/GSvHl+LZAkU+xom983jtvdEA2v96SU8tt2vMYYyY20GvlnMxIMXWjFGL9FuKfguGwx1h4aZu3qvnH1Wfwg1E8HP7VHbOHVa1QvnvR1it8CGKWGjAAXdIc4n4gEtsjUON3mVUZZ56i8+oKvSZ3Q7HVafhQ/PJDfWHQuDDgmibQZjz/nuITBeOEsZRrlZPyFskti6cPRTQYuBZKqzPJvJPJ/Q8ZjXSCZeCTDDGNq+wRGE22F6PNED9re5WQ8rhpjbPjgn34JjH2fVJWQz/5OhloxhrwZjQLL0pqNxBQ7ra5nj6Lx31V//srpgXvcHaZHlavX6TAAMKb6mk7+vCqDkxlp+zLK2MmPEsnaAyMsyKuJrVLZbG7yduLV8g12YoKdmLDNhQ3UMd3uNGUa1V2yemJ3acv4NiM8cJCqBEBBDM2aqGFCTQcEaZubtzFmljE7AslccU/IjlAUYT1rorTud5gZ1szY5iNiWX7F/lhrIyTF/LMsO86YRhz+dUlc89jU79Zmvfg7AODpfnyWi81Dxf55T1iZIeyDRrs47U1j8Wxevl5aqLhvlNpJw7ZL7FatW+nZVlyxAmiGbRnFDdhx1jRi8wS3pWSgetzLw/ua7FoxClUOPBBbDfL7MjYT7mvsB6ryyOJDG32HzynOpEz1jseiFPeyBGAmJOViXmLn0mLpDQWzj9/bXpmmlNh689AFtUKdNOcYd4fUhNL292zpuxLvGye1WS/1JvXqCrnYHZa1NvWf96dcE+FKtTEaR5XaMlMDs1G/UDe7oz44wxAHly70kNKE4mlgEN6nGbTv875xm38zc1QFUe5fDM2WjXtlgs2X0Eg2ufUyt2dOZiI3WamrXc5VbX1xxaq4WtFeasKwlI5jlraVxVAJ8YsOqiYqlKgXgJSWx2IhqMbKmdAsObxKUequcKbwMsAAkJnq3LLOSTqNOr+W60oKuppaRbVlpvpo3QTSQb6xd7XBygnF3kDbu6pBapQg3KVtB6tQ0Svou4IiG6LMldVbEXWe1dJGY/uclMzOdbqVLMX/W/m/7dLBmjZIjOBmLxUDhOTyxxy1NDd2i6NGIRVeVsTwEWsAsC3lMl+D0WjI/jbFf0kbd8JKPD3pZJWQxsNnXHmDsW7mxGi7n7KVPpEWnicBWOZDIwy7+YL7pDbk2Zd8WDWG5WBNMw4a4SY7VrzNreWpILV619bBkOH8BfVkk585zM1FZK9WnZ83fjWbXAtws3VjYTktbAGQMdPFtuKtT+Kh4p1DXlhXvIIdNYGRDkiFwJno/eq0zF4lQ2pgZjmKcT9wJqhimi3/gvNdsKQIMRICkOSflX3ynMGofsY4zDAA2WeKg9J/KsXTDSR28JmKHMyo7SjrcEKktlRj3LQceajJyf9/yRjxoG+ASXU0LM9vbwahzG6Ned/F/eTqSJoxrsibbi+neTR2kEo8UbziYF4+I3RYZumXavp60nKYvgYDoc2lg9y3nGveZyzP/5Z/ssZBj5bE8mVrUBnK3Dt9X3vJBwGI3VL68rt89g1U6VT9OksGtU8Q//LK4kZTz8vMR3xWQ/3Chp0pM8b/0kwpNc/de+LyLLSkMkKsAO8gp6/r5Au1+2bE1Ovm0pQgV1QtdBgkyuC9rVOxEBQHmraMlU6Uz2arxw7eKQagBjUupRy4SIxnXWZy4kVcbzZNP5m7Ic0J4yWTZZMV61VV1pcPy5VLYtnMNzBAAFK7MkBZXvtNYtFqub3jjqT8hv9wAOA0l1SWfjQ1lfUJ8xWKlXfCAI4B7UKKgV2IsR2Y4BNRxelpy4caxgj+44b0d4Ftbco+rzz5k7QMoL1o7KgzFzgsH/Z4KcinXyq7Y/riUKNlSx28V2kZGFJujesW5xMq8JK3bYbjAKy1dDT/4rbpB0vqob1cOfJuCoAMDBhqKwo6B06ejtbN3gj8U43ZNP97KvrNFcv1MO1g6cr1SnveLS50Vp25cZieAuB3pMrNajywAdRl1pQNL39zFGtkf150PrQs36xaFWXpV4DRMaqbv8gmXwrMWPr9in/OvooufmRxPqWd1lZLtISiaYBtSSeWyibjyhWtOnW1LiKlm5U3RU8CrKelytpi5IlMxq+MDSZWl6Jls0bQ9al070t7lRdIOzzAFD2sER8qB0ao07hr7GQTYwPKE+hq/eSwtqZVedPvJVfT1tUJJTH0iclUKr5JwpLDNGxix1l2NiBktBugutbWWMqaNqB+Qkyn2SoX9xIgNQlSKTRTc/6ZkNSzLGMxk16v0lCVC60qpeT4uzbTCMuYbZ41UVzz2IYpxsqyVz2htE67mVZbo5o9brWHrq879Jsos4hRjtvMaB/cE7hgRNyvP1Q1PbId6Is7Nej1NOZiXnKMhsCu3S2Bpu9KraFXNF62xF7IBWB7WKuyTGhWW35/ZJkdD9XWbQ+VcJcGs184zQ+o36Gv3Pzo6bj53ZBrhJBJLvKAhRY6uVU9aHY/N9n2rfkek+ISRLM/G2V2jCr4A1ub3qaOR6NmhdMrs8J+zEOOsRp0jmKJn0x7PZeBaL6NUW9Ba+8FC8E/Cjatdipl9ml5KUOZNdNuMq1t8UaBE2EW+Nwpf7i6b0/n1r10m+9rdXY1i3jGKdMIY5svvmzSyuA9trehCuG+zlvSSX+7zWUos4bs8z5za11FYtBB1XmbvU9k1k8Poh+c8wtMS/NdLuFjNJuhW3eD3svsPUVq/YtW6blekl2j2Hkq2Vh8jwG+4GXqP8sFo+FcH49eS8Oh+7z5bPadsd13yeTgx0OhSSl0jfRVs1Wvq+tlbTqtNfX0PWfgWVp6BN0P94Mh8Pc0IgjKDEFQZgiCoMwQBGWGICgzBEFQZmeY2xb8E+/doexPvA85n/biin1enkYQXM0QBEGZIQjKDEFQZgiCoMwQBGWGICgzBEFQZgiCMkMQBGWGICgzBEGZIQiCMkMQlBmCoMwQBEGZIQjKDEEQlBmCoMwQ5Mzw3wAAAP//Gn/zx3cc8PkAAAAASUVORK5CYII="},"d39d0a5f-a77d-42f9-be29-a2819ba04125.png":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAkMAAABtCAIAAAAtYvKjAAAscUlEQVR42uydb2gTWff4Tx/8QgR/kIILE3DBkQomKHTKLnTCsy86pQumuGCCCya4UFMf0KkLa6Kgrb7opiu4iQvaKOw2CiuJsJIIK01hS6cvukyElUzBJRGUjqCQAYUELCSg0B8zSdr8T5qkadqeD7LdJDPJveeee8659557Z9fKygogCIIgyJblPygCBEEQZEuzC0WAIFuflPSMj3zIfadTR1OECiWD7AgN6cDZRQTZ+ki+bzWWR7nvGL1v/OZ9KBlkR2gIzi4iyHbhhDe2sgq6MSQXwvzHmnLEfMZtVj30ZAhSkWXBfbq/n9FpNLrBS0ERBYK0Oynh9nD/1/2yyn5jD77eEXVGT4YgFUgEL9nFk945LhL1GWM/D+q/DyZQKkg7q+wTu/2N2fvXXCTqNb5xDdIjO0Fl0ZMhSHkkznuXc92eFgHUfVZ2AKTbnuBblAvSxir7yM397Jp+DaBmrOcYkNyeGWnbVxtzFzdqgJ9IgFqNqWNbvIEILTPE7CbJ3fKL3bvVABCLJwD2oZIi7dlghLbPyuwiScW0796jqOz7OACBYzJknXwSfd/p2JkYSqKNiQW/11keVF320lrvzU1dZWQzsBzmHwFxzKLv2hYCeO2zHGGDEmrCdlNa7dDU3L1RRg62UuFQAAiD5Sty24sGPVnTEX2n9ZMHvZ6TJMqijSHNd7y6O3rLwxpzOFKhXxzuXtZzi6VU28KN0ZO6Bx7zftSEbau0qacux22a/XWS7VahJ0PWN/wP/WixvLS7r9I4Z9Pu7KFH79pFs2Xiaap6ePLQan1u4p9MGraB6V8OTZy0iJfco72opNtXaV/7rGfCpoXg5LEdEVKjJ2uqH/vbwV4D510b1Qp7JLi+6R+bxUy6Bui2uW/C2FlHaLmyG7MMhwb992z0XilwbiTwdosHWzfYMXC6f6hJScUnI/3feaLLqCttI5BalPa1z3KaH3zktf1XLT0eGXkkoSdD1mEiXOcnYhcdbHdLwupvDG4VIXzXM/wI9zjVD3XGYZMm2F9C5ULc1NMJy3in+TgR+4fjZrzekEq9Zysr6VMX+2PMNs7W4sfER8P9/4sSKQ/zzUQInVnbCKSK0spjbkfnKSMR47n5oPchr9q7AwbfK0iTWPrVAGCYernxv/SBd/SRhpvh+MrKiuhnewmzbwnlvyENF59mC3K+eicj7ViJmPdEwRkfpes6dRTg6FQt6rL0h5XsZf2iLIXwTQPR6+A/7Gw9aSeBlFfa+PT5ApWlJ58XqYvPqJxWtX1aBz1Zk0jOjRIAQ/54S35sKZpjsuJLS++wARrgnd8KQFyeS27hOtTkyZKcrKTWQG1K+m5pKefCWHQpudP1pJ0E0pjSbj9PhrOLzSEx45uQgD3OqFvxayryUE7YpSbJvdgCDbCXMZ4F6bov+H6bK2nwgaykxr7alHQvSeZcSBwid3p+SFsJZNsobZNOg2t/T5YSbg+vY8XybWDktFto9RS26P/NA8AavmqCI5Oe2Pu/7pf/3RZaLT2QAueG3YuF0+/C7f50kexP2mDp+HXQbnaFUjWvXv5isT+p3EHU+qMsgMfzZFuvOL7ye+4DnDXo1e3fIi1HCtrTne5rt9AmAqlSpO2htM07Da6eua0gW/17q0/Z1/RT/DhNnPKuaxVoyWdu9RT2G6+xWpUjt+jqQhvnMwN/5X/Kr5NFvBcN2sNa+qhtWmyy9FZEr5mgHaESkxb8OBh9sdZINL7gNB/Wantp861wsrbiVVpWrLqUWEMLtoDalaSO2cX08ee1t2DZJqhZYRpqkeasKE/XYKqUSTZZARx8GwqkQsEaUNp2mV2M+c0AcCy9cLs0NQB1lwoaWHJkZDUYyF89/phcCo7SZfvbOv3YXzaCYKfXvQgUnz5LEGen4y1rjj/k5qBuhqsvpl1U+s7F/NntZDz8q5nIWplqnkyuHQDr+IkhAIifws2W3kr8T7bkja3zZIKTBmCuOtguADD7Y3kJC3R1OZf8QtopVLgi7Owu+K3NW3GtQUnW78li/lOyklYUQi1NUGgGNqxFmsfLKcVUMQX5EUlxerQXIO0nqnqyzRJIpYLVr7Rts04WmRpirONzsVUdLpWfsqHrZImowAEA8ZUub9/dLhV51DpyHIhdDc8hp0KuS66ecZth3YtAasMFR89dq3M+1Zr5z8g/PrmjHNZWuzIqzCpBIKXLk45KTZ0ZsQKodtU0R+S+K8EprfoNJwFp/UrbbOmB+pjNQbmtN7nUJs0nc384Q0Awn6n4V0AcH6Sya4LSQ/uwYHOcWf9uvW7WcVG0X/GUn4jRUnI86OOfN6/Sn6ToqzpmSpqhJKWUlH8gKyl1qKEmKJwA28AWad4EVsZUMbr8Y8ZU+w3Wc0YgQLVVBbIBSltVmK+i0qcmfl/TToOr25NFhcfyH1N3sSUlSQr0+zWNTlw/do4tWq3H69qg3mWyDkkTP3tbMoWcNj2MtuoC8NsovyjHxXptcT8gdSdA9zlRS7cMAlCUnr2TjH9YcvxX1XzpAWk6Y5Wuu7yvNsWTRYUZCcBEnbKFP8TFgJnM+mbPjQB1wcLUs51LxZjt1MyYp2xwoyIPyoE792+0afV45tFdWf+5hs1QkhK8UKz5gLa2LIUyTVAULW1kizRPnxb98p/jVAlTdbAHviI1W1UgG6C0VZcTr+g8zzYkfm3wNLh6PdmrCCcpIZ42u3yckoSnotIIiXgMNHsaHJOJ0w8CcMqgrzMrT80cZ2EmwLXAFidiomx6iM5q6puKhgOQHxe/j3L/psP2WOwlpVLV0i3dAKDvIuUofc8GSQ/UfUYWgoGFzVhMTpvyblKjBtizdu53KjQ9uUiY+uo9PqWbsXRLnlm+nJ3YrZY9hPAytrmHpjRFSUoo6RtRUJR0dwNNUGR7NrZFmoQYWSgyVc9CopIUlngXg701PAygXQXSJkrbhEZq+DS4Oj2ZJHDpAXvP6kjw2WTPHUERaCrxntBoGkuQehsKzgDzFVX3owjUWoqBYPCfjc+1ex9TIiKdplpZo8+88p9T+tVpI3FmzJJJPUqlFrVk9dpK4nM5YCc/V2+o9GTxDUBwJrQJqYpvRdmU09qCsFf42yOBhT5c/zwGNQDS/VC5zDTic50SosXim9qlm6EkJYhLipIe1BANNAG0tkWaNIoQuFnFVFGrtREmv5xMpzenlmPE5zWYqnYVSJsobcNurAmnwdXnyTIrQ3A8qx3vBc+vnqzpJMx/xEa/UA5NYXQHDmr6LwRFKeQy6/WMXm/IPI1bfDSsO3hAc9DkXpSiD+2DtL6f1ltuC6mcyLSk5kjzrmGmv5/W6cyukCQGLw3q6X49bSnMHe/S0QABIbLhkxfvJWXehqhmI8TwvOwXKCpji1Jvg547AcsX6TkPenTFa6zwFa88gx0dHR0ayyO5y9gp+UX/b2KFuL4h6QGp6wV4FI60cK2MuyJXqoMek1/cHeyUX9izi3VKZH28p8TkmMS5Tvf3M3rdEYvrb0l8UqhLa1MxR4wgcZFyw/S9BAMAs9Km7jNoTEkq2HNFSZlqSlqxCUqNdUq2SCLquzTYz/TrjgzaH0alRbdFaZGi3ULVWqQpY9znvGKqTFQ65v6UEH6b9AwwGVN10h+7TG1hgbSF0lbWPM59zqQ/2FGIxh5MBxPNOg2uroSTdM5MAQVpUcm5y4Tx96UlJfcXgHYsxCP3jGQ63e7llKF7lP/AO9KRxSnv0pu50T5iNQ9HSa0pkWe15DMz5/1LH1dWViKTA8r3jvOxkIMhAE4VpPAohSybzRWZOskwA7X8M09FqyRYQi25sPGSCcFscYZlpdzFdBbWQJXThpohvZXwTaogu6kluYuZzD3bXwVJzIqqFOejil5zX/oAoZXIHSVDrdfBx3hHji7l5mQCgCNUMREfbE076iPkWHeGdM1Kss7cxYxUa2u+ck2wUlOLfOAdfQbnP/G17TqE2Ssu+Yfkru/4Zz0t0gwUNS4yVcW5hZVSBDdVIJWTKutV2npzF2U1q729lv5kaQDisNl2w2k7qSz8HjLabjidN5yTgUiyqafB1ZUI9TqzKO0UwjbFpUkPhzVmdV5aVIoPXh+0vCMTynPhDL96R/8rus4HRCDYblKct8fMTvpTzCu3q817x9w5PzIxL0FvZp1bfBUAMGoKlnneByYuaEZfGpXHoaZS7wDAaj9Lxx/aOIkwH9Pny0SjOQjwSBRLPy1Va/XNWZuyTPa+tsWkf3l3xipNGtTKpPp1vX5+bfK+pt9KZ2H16irPcjRDeqAhSICA+LbFz0dOp88Yew6qCqZ3wnKZOvOllQiM2zSXReP+9NRbXK7SJZZ+77XNS8QpU0GV1J9pACAsStBbYWgiSu8375HQzVCSkoojvW64CYom3Eq1CAh3Wf6kf/oLpfRKkht1wW5WR0dmROh1GA7X0SINjXGjC0LadYXTZ/+/9Q1/blFXTzPeWgLZVKUtNxp+OmH5xg3jfPQqrcjEqld1mu5Dz0mbebWoasNkbGWyGT9XjydLPOeVRWmDPjsyU+9Vw1mmJ93Qi26Tj/Rc0ZpCo9ReMSBrktEyINteWyhuTanUapW0OOrdR8G/frnfnjExewCOTSbjjgqrqelqO6OGzNjzVTi4CDBAU3uBPM+vnG/3uWDhn6AyH6vPWiUVsbeTOtqT9kmJGbvltWX6bJW1YvFfPwCYj9SVkbih0nvhsXzvqzrFQZyc9A5pK68DhhcBiB7t/tqqdDNqyKiMGJ4RABj6iBq6WH6FbXG35a4NTjzNf++DCK9Vlq89BTIw3/JaD22gkjQ8HbSuJiiKEM9w/j3p0qfCC3L/Zrq1oKbWb7BKibQE9GjAUTZXMBHllRRrw5fU6nScGljmy7TOCO5vveQdZ5WdKu0ikJZTqlPHnkPqTT/3/woGUqPT40y+6RbcP4yFiNG5i3TWtas1sh5vVHBcjyfLZLWe1a/ZJK2FP5jufSnO5+iko2q1mu4FSARlTerWZ5RA9mJKb+5miGy/Zb/MfI1KXS3y3LV2STrlZLWTtz1SVFnHpb5aW7zq/GrUuzfdwUT/bY75yVndxkQlAKrnYF0B7IZK75DV+1czhrhvo1zu+ms18qo0C9Bt6OnalPZVMeNzTMF7Tyc6bpLeP8xES5Wk1U1QtkUgGnog9++s22iGSNdtiwXFVLH6taGPzhIiM6Zq1uvYo4/u3SoCaTklOrXk+1YjXphTdpRX5FnQ+RSI8cEc/yYq6bNGcmOG33V4skxWq5Fem/NQ7aMyx+y88roeWG3j6jxNOqanyvZbo/5ICQdGKAuZUHYLXjrlhDDR2S9eTiR2qfMHdEn59rKJGFGPecRX0+GblYLomuPLSPhRfmwIoD6UOW44NeseA5av/lQzMVzb5tZmSA+Sn5QUgdaeTSxGw1JewjSshtKyHflYXsDKwj5hzGrap1RiGQqr9CkJAOTeygGTqs6tx00Y1zVFSTasCdbZIvAqzEkAJ/Q9mS9KJRL1tUgDdXmu7BVaG+PKo1wqY4VF7y9e60WHejsIZPOUtlxQ9lIWGpu72/i9wD0GOGqgN+ap6+vPXXwbCs4qOzdLzHGJvivDsQumVT8shPxSzqgrf+Af5h/lDNfyUfZJBESpcOJV39Gh+T6YSPGcbNMtdKZji55vGc+LohHM4wobaLRW39zcX7X8q+LGCLKnutAWQ97C2DDLcshxyTV4xlQ94nsVCdW2ubUZ0gPpdaCWTXLNteXi84CsW8Xb6lWdnQTAi/w6LYcm6I4OzYhcpXlZwJbejA8Q75uY3wq3i0pvonKNOiuLT6chNqn3N0VJyinpkYaboJYWAdH3naajQ+/+F8SFAAfADNCZJMzZMe2FwsNha2uR+s1paJYrGOOuFfSBfThmN/WptoVANk9pywljjywuzWdrLll44PQA7bhmKWgLad49YraMXLOb6EHPvy30ZKnMIlnByCCVeBGc+EZveURZBqj8UVeZaCY9XBugSi6bEAd7KIDImzytiM5PhoAc/Eobf+SeWPskEfrR4qHdhU9qlmKRnGzmDWSXklGyIMYqzMcKSmw4kC+JTynxqWdkQD+xaK3lEP2UGOUAiL7qU4JNkB5IsZcA3T1kS3tIeo+5WX+kuCeT1PEiIb/gJp8CeZTRJgLu6zlV+nvCck/vLlpPir3m17KxS83d8rLsYLOmfpqiJGUtyy65IfnXsQaaoIYWkYTpBxLRN9izN+S5FVx7/7XPei7mumZUr6tFGkQ5/aj4GLnU+2jw+qD+uwBlZqiGdLINBLLZSlsOdZ/RRoA/mHkegPh4hL0A7J/e0d7ckqaEn/upC1HmJ+/kuNN5TuWeFVowu5gInuscvLv60tW/21XiqhMuS3f+bEmZpYv0wJ/9qqd0GxyiDAR4XuQlHlIn3VbfWOSuxUJYwrEx/oJl+EuB/AzI4+7g+aIjTl5HOSCs3doNbzSC1AMEpGSpTSaCi+qxL2ZfzQ4f6Bguvogat9ZyOmL0XznANB2uIS5vXHogRmeBGKK0rVT/hJIkVtp9qrVfGuBuOPoWqNXl4i/M7jPeseduy0nCIsTGFmyWcz3C5xrYb3TPsNSeotlsQYKj5SeJUknZkdR0dlFzaaaSlEOzv7yS1toENbQIYRi5YRB+52zHef340hK4Ry706x+Ru1UUO+s17l9ni9StR09GOr9xr5mqr0uaKqPrJNWYTraBQDZNaauxh3GG/PbvrT20RgNJFWVxxCaZAhm+8o5d4sifnIb9kHod9NxPWW82YG829NEcYZ93Wiy90yEpTnt94XiFTS2XCeh2huveR3KDAmK0JY8BTu+Ka9rB0mX2k6UPirb639W2K6sx6a0ITll8XLKlZ+GHHAQAdSNcbi+dofbnHRejPGPXcG+p8kNPmvIMh/r3kzWgNVXOwg8pSlq1PJWboLUt0lLKbdvadIFU3E9Wt9K2Zj9ZDU9TocyXnc4bzqkAH2nswfcb+qRNNXXSbNhfetCl2m8wn6TKBx8q5ls7tejlFuuMczmfQF8yMa0YdZPaUwDAixuyzz4l/DJ4oOPA2AwvD3CHDExNgXmD0gNh1iv01rKK0AzeBoaPaDRGX1AepufOTufTZbIOgecJV98Rc4mFoIdg2WNlR7TKJjwwH2peMmwX4z1Fq9skRt6vNVeYA6+xCVrbIpvJFhFI85W2mkmnT3mZJs0GK+fO9Jgu2GwXbdbjtLbB5LKV9iU5d5GAIX8dEU48YAXCNteqh22mzxEw/r60AWOy9ICPtl22Eut7nlP90lNiQ6L4RIMNGpOl40rixKjtKFR5qpwc81J1PdQq7OwGw68VGmjJe3w9j+9qO6o+nyx9Lo/RKzbWBK1rkc0ck7WRQCqNyepX2nZ4Plk8yBI5ZVj63Wr+NVL3JBq0dff8wI92E9UOiSk2xNPsep/Z2oxpscJHIzbHkyXDd4xkl5buNTsX4q2QnvIkT3qcL75to2YX30zb+kjtYdpw0RupFnws/W6Eo1NL6w41qj07Ozlnk02Xg1/Zrp5shR8nyh65tJ4maFGLbO7sYvsIpIIna0Bp2+NJm8nwLTN91Dp6Y5Q9xToDkUaejQzt3kNFr7nL7BXXoUjeU2QrHqyer1KjRNPsoKxkXTQzwDC3wi2X3sqSz0wW9ajwLYYZYOiuVj0zuqKs+XG6pKMte0PIQfc6+A/VYxHi8lxy+3qyJKco6Ti/NVpkEzwZSQ8wzMBkuE0EEpu2DTBMn5Yo58kaUNq2eWZ004AtUMZkPF670n9MxuObYI6UgLct56bWJT3l8uRW0Ijkui7+WC0ivkHJkUho63bk6p5sZYWXLV8jeUAtbJGtTgsE0ojSbj9P9h9of1TqdZzzv0ulVm/C5gr6mJ0CwTsrbG3prR0o1u4aoVrXxbuq5wdBt93QC9sa2nCBggbygFrYIluejRfIDlHaWvkPiqA5dFvHhkC46edSKIstRmre71wE6zUrtd1rSg2NWUFw/oFKikqLngwpk59q/N5JSxO+mQTKYkshBe5OSL1O9rh6+9d1r5G9SUvXfcH32O6otOjJkNLDMtZ1lfKcc3DLKIutE9vOOm2PqNGf2R0S21JnXKPdHvYGDstQadGTIaVR0Zfcjv2uscLn7iNtaxIE1zUXOe4e+69qp1R5Dz1210H+POZ6hkqKSoueDCljJkbvT3XeYl1P0UxsAZMQ+pmdPOj1XqV3lElQ9Y567nVOnneFcPIAlRY9GVKaQ1b/48Hp41bfa5RFWyM+tBqDg4E7ZnLn1V075A8Ypo3nfCLqASotejKkXMzLzQzGFnCOsY1ZFkJvB4Ozo/SeHaqk9FUuOBAL4RwjKu22YBeKYEPsRLfZ1o1iaGP2UOaLO3y9XEWdsmHKACotjskQBEEQBD0ZgiAIgqAnQxAEQXYyuE6GINuFRISf57KnPnTqaIrATG0kQ0p6xkc+ZDUlmgBQoydDEKT9mJ0wzU5kXxi9b/zmfSgUJOO8uBv9lke57xi3U/U6VlZWsJERBEGQrQuukyEIgiDoyRAEQRAEPRmCIAiCoCdDEARB0JMhCIIgCHoyBEEQBEFPhiAIgiDoyRAEQRD0ZAiCIAiCngxBEARB0JMhCIIgCHoyBEEQBD0ZgiAIgqAnQxAEQRD0ZAiCIAiCngxBEARBT4YgCIIg6MkQBEEQBD0ZgiAIgp4MQRAEQdCTIQiCIAh6MgRBEARBT4YgCIKgJ0OQDWRZcJ/u72d0Go1u8FJQRIEgCIKeDNlSJIKX7OJJ7xwXifqMsZ8H9d8HEygVBEHQkyFbBonz3uVct6dFAHWflR0A6bYn+BblgiAIerL2Rnxit/wSStVs7APnht2Lqe0pC0LLDDHWL8nd8ovdu9UAEIvjoAxpDakUygA92TZiOTjSURWTrxljBfGhRf9T58gZWlWzsTdeYvijzMTTDe11ku/bsjU/QJtGbgfF5Y34Xa313tzUVYaQWyHMPwLimEXf1dRfeDpRVKGJ0NrHoYmyHyEAb32mYoX4caOFJExoOjo0Bw5oOjq+9UkbVy+S1HR0mB5Kla45eOBAhWvKE/qxuk3ZqNohaVZ2Ji+nGLn2zNTLvLeT4vRoLwA4+Gb8hAFop7Du++J/sgTBTr/bcBnMXVY04GpOXT/Gpi/T8pu9Dv7DmlT4nxiC0Fr/WGrSLyf5cRp62WlxYyr2j4NSasb+GS+W7txVCgiz92Wy0V8R/dYuII86cwS1PeBHFekZf19q3W9yym+e8MaapWBFGhu5I/d4o6/SL0RuVb+mAkv3jIrkRvOsRzIevmclAeC4d2kF2Sh26OxiIipw8hCI0eWPCVT7DdZzRiBA1fi458pw+KKD7V73nepjNgfltt7kNno2ZLcyzQf/l/PWLsLwk9vZDfB0jF2bFI1ytzhJinqeCE0JKsWHVutzE/9k0rC/5ns+SdFXNU9EfmFmj8p/3QvhIhmq4FOMGXeYuxptYekfv+cViDNO7kXbq/u6pAewO6MMu1tXQlJnbObXldDYTrW66m2de9UNdShVnvyyGqemhia94xQ8FnFMhrOLTSa66Jf/HKe0xX3qYA98RWoanJN/6nE+ouxmpi57SZrOWKXrLu+rTZENpT+mTPrc4aLZd2zz/skbU/xNI9GMGdfh0KD/no3eKwXOjQRqnMV95tFdCdZsCEjmhEH++7Mv+L6gYfjg9R5zH9m4mIgTbv6eczLA2b5oe3Vfn/Q2g11N1uEmamwzUNHHLBSuCqMnazZiZEHu1wylzcZgKelZKL04lHgXg73qxiL2FP/npECYmO4671f3GVkIBhY2dcMVsSYD1SEje9FK7230K1NPJyzjnebjROwfjpvxekMq9Z6NCfGPWa3yX09wIc94JGZ8rqNGpjmLc2p6yMYe16rQimzIOLKhDI1maWyjCv9W4F4oGniIYiCWWMZ2RU/WRCSBm1XmFqnV2FyY/HJSUPQstRwjPtc0NMsAQui+BKdobf1GUksNQHAmtAlxdCrEPZH/Gs4ZldUmJT1Eo9MdzFv8T/ztGmb6+7/u76d1OmbYNZ9X0sTf7hGzyfL9mP10f//pYdNBJYMmEbQfHwu9cMs3Mv39BntARTYo6LLsZQxDiiv7zZ8TDiS4Jx7rGVP+iCwR+nm4X6mL/oiu/7SLW6tKpu799IGOK57AJZP+YMcBesT3KpVOLTlwRKfJTQ5ajvoumdJfpTuiN13yRVfdaG5CwYNo9KHd9HV//xGN5sig/Ul+vJKIBn4c7j+i038tS8l0zh3KGVZK865hWeD6Awf1wz+HWhLilxWCkuZwQM/oNEZ34PZwujoT84maSitx7nODBzQ6WYW+HXHPx3I+UxJz/k9RuXSWRE4qSn46RiL6eGKY0eloRaO+HXH/nSinsZkb3vKyeGW9PSAL/2G0igwTUd+lQd0Rff+RA7pv7L4X63OviQVH/yNlakPVqenmRQnKCi2tUXS/TmNyP3IPp08P+JFbLV7i38DEab2e7pd147Qr+Dpbkmo37hR24Npg8i+bUnV2Op0Q8DEe/tVMDEzlr8cu+Ye0ZBdBnpgMxyLeiwa6l6F7zZNCUv6GkIM5TJIEY/tzKbbgNPfSTC9tuDi9lJNOUnrBPDbnHGKYPlp72OxciC39aTMo95pvhQsyEPirAGCbS27kyv64IobxEhkf9Pnp3NIng2zelS+nlMk7q/9dNn0DCLNvKedTajXVJbkwSoHR+6axsoYc600HyLayYS2pRy5Yusy5q/RKVYb8si584B29clW8uakozyeV5CC5QdMSI34Kp/MDJgfkt7NVS85dJgCAuqF8KnrNREHiTCahgCAIepxPrn1DTgnfTLO9yl2KZoZvKrHE2YyeLvnMBNCOBeVVdNIAkP2e5kqPd6Trm5v4UE4I8Wk2PZ13lY/4lKWuU/5Y1dJGpwwEEKe8Sx/TWTiRqVPKLGBOIeN/sgXv8FeJ/FLFps/TsPoTgpPK6dSFGruyEksXb/X6lZV40EblyzB9zdpPKPqQLWd8+iJRqBsFnTvzE9l8seTS1In8/pX54XJCi0+fVz7oHuWjXuUDc/qDpT+s5FrJk5FfFdmGkmvfWObGncNO9GQZA1Ews34zXGDgqKt8MpTu1IT596UYN8oQis4l50YJo1dc8p5QPux18O8iUydIAMLxT9ZwlEycE73mPtYvrmVSyffGeEcfUax5SiHLOYDk3FWGGajp3+hfySqerItevVhLABwyOIKxZLEpLOHJssV757fKQsp0YKU/M5PR3Fy4TfBkK3Iz5bWs7LSyXqHQk2W/PB5QqpJrfd6kTYMSVcSXeI5fynxFTFGAQk+2em/4BlXgDzKWrtsZzm8C8x+xrD0iAIhRLiP+2B+yN6R/UqKctMzTHjf9cxcBahRs456srBDSFys5wB9jYW4uHMvRkNKlXZo6WlTytILlFrLonQI3Ew+ysrAuZ4O9N/506JAJCQs0dlX4eX4l7pcH7mtRV/5PpBt07dN0hEqM89U8WT4lri8jtKw+ML/KQWFMmJsTYmvCv5gb1i5NDQB0O1adcOkbdxK7duAiWXRBSBu48A9UeuZn+HOL+nDuXKDIPYxZbtCpN17ZNl30ek51cucmOAnoL7XqBc/EUUt8f8LzUgmoH4zSb13sIxEIllIWYCQxDACazwomzhKBcZvmsmhUEvZSqbg8qLnE0u+9tnmJOGXS569NawgSICC+BdhXYhWAGZ9jmiWP71xzV+nVuUVpxmE0aCb7bJ57zrK5hV1W/5ueKGipdNn2aki52mHxLdD7gCB7CBgbOWYSr1hMtJ7qoh0r/s1YZWcGzxET1yThd074gaJACNwKj95kClqFHPLHqCgcotLiV6er8lyUgM5rkAEtqQJQkXTZbBEVMx6NfBvTZBVJs48EEAKvRID8pjXqCyKp1Ke0gvDB2xIAq6cyS2+EbMe9GY2c9wUBGJrKll9FHjECBMLRlHlfq5bqygqBIvcB7CKoPqJ6ad8H3DMA3XrtvkaKkuCfuGVh0T2Zyu8zrgmr5kl8imbgPuecEWzdVPFid/C6BGChDq2qvY4G4BYiItAVU4Yc/Mqo3KMSgsvcYy+fllIgtLUP9mvk1u9m0h+IM54AgPEImdPMpO4rgGtj/gUbPaAqd+OOYud5skSUf6zMOn2Z1d29hBpY5su0Qgjub73kLXvPZS/ZDdGAW/Y33zAqAMOtZPwnUKtViVcm/hqlfh3gFwGOW5T0ARsft6ZU6oqJImrDzaghc4UYnhHknn5EDV0sv8K2jXRUxFGH91fhwP9cgyc7w/OjVJkaqfZR1Pto6DHPv4pGZ3ku97Neq+f89ODtgOt0wKUsR9p+nXIeqz1dMMVdG5x4mv/eBxFeqyxfewqSUsy3vNZDZb+IPmanrtmFRad/nqU6Oa9kdZbYpK4iuqnEi1AgxIvRaHCBK9N6u6vnpO9Sa7tV0mLQtxCNRPnQAr8+2b8SFIev6VSXWtpVCha5Ndz/KPteLCJr0vtEvqdsmvTWI4TO3apaSyslwnIgeVDTWHqwKCi9uCheXB+796iV4kYloAqt/78hxS8Gxr4RsrVOigAwK0kAZG2O0njSaH+dffnM1f8nNT2+ms9cILQcaf4/VbEwS26K8D6LOgeoMjeiJ9vevEjbC1Z/ePUtnSVEprMYU7Nexx59lCDUBAEg8E9yrtylSu9IUXfRNEDiCR8AoL7SpnW6ihfLXpOXctJt6OlqRwmRAxYjBANPxzyz7OSxkpYiwV0zWX6M6H5wjP7Pzv4guv5PP5ZjIg23+NjpILfAcY+D0/Oc6xtL5z/c6BeqWgdTxSPOpxMdN0mvMtu2DrqN7IB9eFbyzHJ6cMKFYIldEe+5sW8tE1Gd7adR6wXWZnR10GN15sq88IwcG/aA0XljzHqKtc5YDpgD67j/E1RI8Eln8umveP0niRZJr5G0ofKllR42ZZ9kCjY6GyrTHFbXX6N0vd+h6RubWyazvjcY2V3PtpwKSZzSJzyCa6d6MvG5kpt2XL+agA8qgurNfOj9xWu96Mh88jaqjLpyrswhvSNtbWCXG4rtlXU3+am8aj7nfQDE6izTp1RiGQpcoXI7Q+ytedRSblxycdoxUGekFi/dh1LCdUP/jyHqKj89nh7jZLPvPqUSCUgtjLGS1X/GYO42mM87E/NjDDMxORsd/YJqvVNmThpgNihdHxwEyikUzyAJE8f6J55SowvTjv8qVclG0MlUIvFJvY5NAm8D1r5hn2T0in6zMiu7ZmmXE4ldNUQ6+7VmAB9EYlLhfCQAoaUIeCQllpNboZNVKi1xsIeAgJRIrrcmyeXcdDxSewrgAUTeSNBbv4NOfydFa4myzRFPpqDugxJU+6hsVJEQQpx+QFO3MOFTvsA+yv8xHyLRh6XZaVn4UmhWHqqvjqXynNwD+3DMbupTZVUvb9SVj8AHpPyBXY76dnYSANE3+UHjcmiC7ujQjAQTKX7eCwCW3oxhFe+bmN+ihQV9HQAgOveUjbvn/qrpXx1uTJz1KkMJ4yBd0kYIwSshADAZ1qbqMp1MClg7Xc+WxcCdoLDq1/sGTQAa1SaOLxUGWGPx9r7F4JgcEJgG/5stX9ZeSI+tnb+s48hBacHrkwBOmJj9ubGITOiXTuvjGkYQBGM5SwD4grn56ouunq89IgB11E4DcI85MTeguaIZmWnHqLxSab8w2LsBZkNCzu6CVDxWHGPnK5/sCfKEdYKVhTXD5whLcFH9nsrnCXwstgYG9hhVvjm8wYUcCb/yDNLuaB0SeeX33IcekqhbmIF5IaemYuQpAMFa+gj0YTvSkykH18qDnbz8Dki9jwavD+q/C1BmhsofdRVcCbnDtQGq5HANuigTAP86v3O+4CafAnmU0SYC7utrdi3x94Tlnt59tqAvSbGXAN31aX7NAWmyqG9/SggPRyz/CwKQ1j+c5tU1+bR9z1xJ0UqS3vRs+jirROhH20RmEJdMdKtkn7DodD7IGLHUU24aaEsftTktvs9gUTaWGU4yJSKSblrJb5zmnmaqMnFxIj2zFF9OUHtU6f9P/7doDJFc/Ui2e18aDACwMM2lR3WvfWOXlHjgYzz+ATTKV2V828ciw5pxn2rDJbe1CzznWM+/itX6JPpuurVnBuWSd7PuWwZiZmzkl4xFSz11jc3brUebHyMk8516RSGk3yl6u1JpKfaugwYPey2QMc2vA/ZxtyL/eHx1JuMwbSWUdzLdxO28r/zP+3gmQjpmcw+RcJ9lf8vsCRMfON1H2MGuYo3N4UfbxN+ZEkV/s9keEWbfpLUrP/hYbY4rHrZXcl2zBzIjddE3PkFesZTbJ5pM5ckva1wS4rzLdHQ4CEZyX0WhZQtcOJ3TzXrvmYn7TudsIhtzj43NktZbNsPeijfuKHZIjmZme0oVcjODlTzX1T1npfYqFSTu56Z2Tx0tPg51yX9Gq81sSouFb5m1XVqmj2GGJsPxUpnQRE6GcZOJZfYPlKSLNp51+p/HC3Ky80T0MTZ3izUcJshehhkw2nyRmDBp7ALoMjhDyZjPSJ93Os8atIcZpk+r7bU6F+KNFrmOLPzVxlpwMAO2sicyx+Ymzxq0BEkPMMwJm/d5LHzHSEL6aOAiQWXLUJhvrWRax5/7HUM0SWiZAYYZcs7FlqZ/YAggtGf8S5ks9jUc447SuheP+MetTEa2VkcgkqsDMW6SPcHImjPAGC96I/GmSq+okErVnpQTQmYXR06dCvLNK5Q2/txrO6YlumilCzjnfKNrgsjm2SeFSWsvSchaxBgueqfvGIv6aTwScFj7lO8ZYKzj/siHMhqbbrJeZzgWnrpokH/0MEEeZSe5WJm65zdHL5luDicXq7ShpQqjfAWhhRyFH4SKhUnTvQxzWEsPOdZ6aLUbdwgdKysrODItuRokzgRCnxnMX5Qadr0XfLMx+piBLLOOIt4fPHBa4383ZazvvJxFVw/lNHCiow/PQlJQchZiLcxZQOm1ZadMgQp7BFIC9GQbw/vA8GcmCMSnjteTJSz83NMTsIRDNgolmZFnyBcijMdINGMoPQRBT9Y6xN8GD9xhwsL6vZHsBVn1X6JzAC0PgiAIerJN9WW+bw94B5amz6wrUzYRPKd1aALcVRr9GIIgCHqyzWY5NDFgg1+40d5avZL40NI/Mzj3uxn3iSAIgqAnaw9K7XquQCqRWMfVCIIgCHoyBEEQZKvzHxQBgiAIgp4MQRAEQdCTIQiCIAh6MgRBEAQ9GYIgCIKgJ0MQBEGQFvL/AwAA///ZgGZFo7RjAQAAAABJRU5ErkJggg=="}}},{"cell_type":"markdown","source":"# 6. Bias and variance using bulls-eye diagram\n\n![Screenshot 2022-05-24 081851.png](attachment:fff0786a-2bc2-4b4c-9075-e19ef2fe0a2c.png)\n\nIn the above diagram, center of the target is a model that perfectly predicts correct values. As we move away from the bulls-eye our predictions become get worse and worse. We can repeat our process of model building to get separate hits on the target.\n\n### underfitting\n**In supervised learning, underfitting happens when a model unable to capture the underlying pattern of the data. These models usually have high bias and low variance. It happens when we have very less amount of data to build an accurate model or when we try to build a linear model with a nonlinear data. Also, these kind of models are very simple to capture the complex patterns in data like Linear and logistic regression.**\n\n### overfitting\n**In supervised learning, overfitting happens when our model captures the noise along with the underlying pattern in data. It happens when we train our model a lot over noisy dataset. These models have low bias and high variance. These models are very complex like Decision trees which are prone to overfitting.**\n\n![download (1).png](attachment:00dc304d-3570-4804-8aca-cc3c6298413c.png)\n\n*credit - GeekforGeeks*\n\n## Why Bias Variance Tradeoff?\n\nIf our model is too simple and has very few parameters then it may have high bias and low variance. On the other hand if our model has large number of parameters then it’s going to have high variance and low bias. So we need to find the right/good balance without overfitting and underfitting the data.\n\nThis tradeoff in complexity is why there is a tradeoff between bias and variance. An algorithm can’t be more complex and less complex at the same time.\n","metadata":{"id":"PTgaeWpbqIof","papermill":{"duration":0.08266,"end_time":"2022-05-24T07:43:51.05887","exception":false,"start_time":"2022-05-24T07:43:50.97621","status":"completed"},"tags":[]},"attachments":{"00dc304d-3570-4804-8aca-cc3c6298413c.png":{"image/png":"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"},"fff0786a-2bc2-4b4c-9075-e19ef2fe0a2c.png":{"image/png":"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7. Total Error\n\n\n> ## **Total Error = Bias^2 + Variance+ Irreductable Error**\n\n\nTo build a good model, we need to find a good balance between bias and variance such that it minimizes the total error.\n\nAn optimal balance of bias and variance would never overfit or underfit the model.\n\nTherefore understanding bias and variance is critical for understanding the behavior of prediction models.\n\n*from* [*Seema Singh*](https://medium.com/@seema.singh)","metadata":{"id":"JxoV0MHvrYMg","papermill":{"duration":0.079858,"end_time":"2022-05-24T07:43:51.38031","exception":false,"start_time":"2022-05-24T07:43:51.300452","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"# 8. Notebook Setup","metadata":{"papermill":{"duration":0.08028,"end_time":"2022-05-24T07:43:51.540617","exception":false,"start_time":"2022-05-24T07:43:51.460337","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"## 8.1. Loading Modules","metadata":{"papermill":{"duration":0.079766,"end_time":"2022-05-24T07:43:51.700605","exception":false,"start_time":"2022-05-24T07:43:51.620839","status":"completed"},"tags":[]}},{"cell_type":"code","source":"import numpy as np \nimport pandas as pd \nimport matplotlib.pyplot as plt \nimport seaborn as sns\nfrom datetime import timedelta\nimport warnings\nfrom scipy import stats\nimport random\nimport os\nimport plotly.graph_objs as go\nfrom plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\nimport plotly.express as px","metadata":{"papermill":{"duration":2.556751,"end_time":"2022-05-24T07:43:54.338434","exception":false,"start_time":"2022-05-24T07:43:51.781683","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-03T23:42:13.971019Z","iopub.execute_input":"2022-11-03T23:42:13.971256Z","iopub.status.idle":"2022-11-03T23:42:13.976440Z","shell.execute_reply.started":"2022-11-03T23:42:13.971216Z","shell.execute_reply":"2022-11-03T23:42:13.975427Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from sklearn.metrics import mean_squared_error","metadata":{"papermill":{"duration":0.281133,"end_time":"2022-05-24T07:43:54.701424","exception":false,"start_time":"2022-05-24T07:43:54.420291","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-03T23:36:19.019112Z","iopub.execute_input":"2022-11-03T23:36:19.019504Z","iopub.status.idle":"2022-11-03T23:36:19.150647Z","shell.execute_reply.started":"2022-11-03T23:36:19.019461Z","shell.execute_reply":"2022-11-03T23:36:19.149536Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 8.2. Configuration","metadata":{"papermill":{"duration":0.080642,"end_time":"2022-05-24T07:43:54.865613","exception":false,"start_time":"2022-05-24T07:43:54.784971","status":"completed"},"tags":[]}},{"cell_type":"code","source":"warnings.filterwarnings('ignore')\ninit_notebook_mode(connected=True)","metadata":{"papermill":{"duration":0.126952,"end_time":"2022-05-24T07:43:55.072878","exception":false,"start_time":"2022-05-24T07:43:54.945926","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-03T23:42:15.501562Z","iopub.execute_input":"2022-11-03T23:42:15.501983Z","iopub.status.idle":"2022-11-03T23:42:15.541535Z","shell.execute_reply.started":"2022-11-03T23:42:15.501959Z","shell.execute_reply":"2022-11-03T23:42:15.539783Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 9. Diving Deep into Code Examples - Generating Data","metadata":{"papermill":{"duration":0.083229,"end_time":"2022-05-24T07:43:55.238945","exception":false,"start_time":"2022-05-24T07:43:55.155716","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"## 9.1. Lets Generate some data","metadata":{"papermill":{"duration":0.083441,"end_time":"2022-05-24T07:43:55.406926","exception":false,"start_time":"2022-05-24T07:43:55.323485","status":"completed"},"tags":[]}},{"cell_type":"code","source":"rows = 1000\nrandom_x = np.random.randn(rows)\n\nrandom_y = (((random_x ** 5)) + (-2 * (random_x ** 4))  -4.2 * (random_x**3) +20 * (random_x**2)+ 6 ** random_x +2).reshape(rows, 1)\n\ntest_df=pd.read_csv(\"../input/digit-recognizer/test.csv\")\n\nsns.heatmap(test_df.corr())","metadata":{"papermill":{"duration":0.093743,"end_time":"2022-05-24T07:43:55.584805","exception":false,"start_time":"2022-05-24T07:43:55.491062","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-11-03T23:42:17.307803Z","iopub.execute_input":"2022-11-03T23:42:17.308031Z","iopub.status.idle":"2022-11-03T23:42:52.887443Z","shell.execute_reply.started":"2022-11-03T23:42:17.308009Z","shell.execute_reply":"2022-11-03T23:42:52.886327Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"random_y.mean()","metadata":{"execution":{"iopub.status.busy":"2022-05-29T11:05:57.138756Z","iopub.execute_input":"2022-05-29T11:05:57.139173Z","iopub.status.idle":"2022-05-29T11:05:57.144575Z","shell.execute_reply.started":"2022-05-29T11:05:57.139126Z","shell.execute_reply":"2022-05-29T11:05:57.143894Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#### Adding noise","metadata":{}},{"cell_type":"code","source":"mylist = []\n\nfor i in range(0,320):\n    x = random.randint(25,100)\n    mylist.append(x)","metadata":{"execution":{"iopub.status.busy":"2022-05-29T11:05:57.182949Z","iopub.execute_input":"2022-05-29T11:05:57.183387Z","iopub.status.idle":"2022-05-29T11:05:57.187889Z","shell.execute_reply.started":"2022-05-29T11:05:57.183355Z","shell.execute_reply":"2022-05-29T11:05:57.187269Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"random_y[0:20] = random_y[0:20] - 100\nrandom_y[100:140] = random_y[100:140] - 30\nrandom_y[900:920] = random_y[900:920] - 20\nrandom_y[200:520] = random_y[200:520] + np.array(mylist).reshape(320, 1)\nrandom_y[500:520] = random_y[500:520] - 50\nrandom_y[600:640] = random_y[600:640] - 25","metadata":{"execution":{"iopub.status.busy":"2022-05-29T11:05:57.292837Z","iopub.execute_input":"2022-05-29T11:05:57.293134Z","iopub.status.idle":"2022-05-29T11:05:57.301372Z","shell.execute_reply.started":"2022-05-29T11:05:57.2931Z","shell.execute_reply":"2022-05-29T11:05:57.299974Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 9.2. Visualizing Distributions of X,y","metadata":{"papermill":{"duration":0.080593,"end_time":"2022-05-24T07:43:55.74647","exception":false,"start_time":"2022-05-24T07:43:55.665877","status":"completed"},"tags":[]}},{"cell_type":"code","source":"sns.set(rc={'figure.figsize':(15,5)})\nfor i, column in enumerate([random_x,random_y], 1):\n    plt.subplot(1,2,i)\n    sns.distplot(column,color='tomato',fit_kws={\"color\":\"indigo\"},fit=stats.gamma, label=\"label 1\")","metadata":{"papermill":{"duration":1.102155,"end_time":"2022-05-24T07:43:56.929727","exception":false,"start_time":"2022-05-24T07:43:55.827572","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:57.596877Z","iopub.execute_input":"2022-05-29T11:05:57.597501Z","iopub.status.idle":"2022-05-29T11:05:58.35227Z","shell.execute_reply.started":"2022-05-29T11:05:57.597447Z","shell.execute_reply":"2022-05-29T11:05:58.351351Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 9.3. Train Test, Holdout sets","metadata":{"papermill":{"duration":0.085834,"end_time":"2022-05-24T07:43:57.099381","exception":false,"start_time":"2022-05-24T07:43:57.013547","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# Hold out 20% of the dataset for training\ntest_size = int(np.round(rows * 0.2, 0))\n# Split dataset into training and testing sets\nx_train = random_x[:-test_size]\ny_train = random_y[:-test_size]\nx_test = random_x[-test_size:]\ny_test = random_y[-test_size:]","metadata":{"papermill":{"duration":0.098271,"end_time":"2022-05-24T07:43:57.282727","exception":false,"start_time":"2022-05-24T07:43:57.184456","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:58.354479Z","iopub.execute_input":"2022-05-29T11:05:58.354779Z","iopub.status.idle":"2022-05-29T11:05:58.360777Z","shell.execute_reply.started":"2022-05-29T11:05:58.354736Z","shell.execute_reply":"2022-05-29T11:05:58.360149Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 9.3. Plot the training set data","metadata":{"papermill":{"duration":0.088324,"end_time":"2022-05-24T07:43:57.465216","exception":false,"start_time":"2022-05-24T07:43:57.376892","status":"completed"},"tags":[]}},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize=(12, 7))\n# removing to and right border\nax.spines['top'].set_visible(False)\nax.spines['right'].set_visible(False)\n# adding major gridlines\nax.grid(color='grey', linestyle='-', linewidth=0.25, alpha=0.8)\nax.scatter(x_train, y_train, color=\"navy\")\nplt.show()","metadata":{"papermill":{"duration":0.367888,"end_time":"2022-05-24T07:43:57.918023","exception":false,"start_time":"2022-05-24T07:43:57.550135","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:58.362008Z","iopub.execute_input":"2022-05-29T11:05:58.362452Z","iopub.status.idle":"2022-05-29T11:05:58.624394Z","shell.execute_reply.started":"2022-05-29T11:05:58.36241Z","shell.execute_reply":"2022-05-29T11:05:58.623722Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 10. Plotting with Simple Regression","metadata":{"papermill":{"duration":0.083144,"end_time":"2022-05-24T07:43:58.085212","exception":false,"start_time":"2022-05-24T07:43:58.002068","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"## 10.1 Developing model","metadata":{"papermill":{"duration":0.082441,"end_time":"2022-05-24T07:43:58.250342","exception":false,"start_time":"2022-05-24T07:43:58.167901","status":"completed"},"tags":[]}},{"cell_type":"code","source":"linear_regression_model = np.polyfit(x_train, y_train, deg=1)\nlinear_model_predictions = np.polyval(linear_regression_model, x_test)\nlinear_model_predictions_train =  np.polyval(linear_regression_model, x_train)","metadata":{"papermill":{"duration":0.095682,"end_time":"2022-05-24T07:43:58.431918","exception":false,"start_time":"2022-05-24T07:43:58.336236","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:58.625498Z","iopub.execute_input":"2022-05-29T11:05:58.625748Z","iopub.status.idle":"2022-05-29T11:05:58.631531Z","shell.execute_reply.started":"2022-05-29T11:05:58.625717Z","shell.execute_reply":"2022-05-29T11:05:58.630738Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 10.2. Plotting simple liner regression","metadata":{"papermill":{"duration":0.084249,"end_time":"2022-05-24T07:43:58.598829","exception":false,"start_time":"2022-05-24T07:43:58.51458","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# Plot linear regression line\nfig, ax = plt.subplots(figsize=(12, 7))\n# removing to and right border\nax.spines['top'].set_visible(False)\nax.spines['right'].set_visible(False)\n# adding major gridlines\nax.grid(color='grey', linestyle='-', linewidth=0.25, alpha=0.7)\nmain=ax.scatter(random_x, random_y, color='grey',alpha=0.2,linewidth=6)\nplt.plot(x_test, linear_model_predictions, color='firebrick', linewidth=3)\nplt.show()","metadata":{"papermill":{"duration":0.35295,"end_time":"2022-05-24T07:43:59.035669","exception":false,"start_time":"2022-05-24T07:43:58.682719","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:58.633396Z","iopub.execute_input":"2022-05-29T11:05:58.634194Z","iopub.status.idle":"2022-05-29T11:05:58.919402Z","shell.execute_reply.started":"2022-05-29T11:05:58.634146Z","shell.execute_reply":"2022-05-29T11:05:58.918786Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"- It clearly underfits.","metadata":{"papermill":{"duration":0.085948,"end_time":"2022-05-24T07:43:59.209652","exception":false,"start_time":"2022-05-24T07:43:59.123704","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"# 11. Functions to calculate","metadata":{"papermill":{"duration":0.0855,"end_time":"2022-05-24T07:43:59.381157","exception":false,"start_time":"2022-05-24T07:43:59.295657","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"## 11.1. Calculate Bias","metadata":{"papermill":{"duration":0.084677,"end_time":"2022-05-24T07:43:59.551043","exception":false,"start_time":"2022-05-24T07:43:59.466366","status":"completed"},"tags":[]}},{"cell_type":"code","source":"def get_bias(predicted_values, true_values):\n    return np.round(np.mean((predicted_values - true_values) ** 2), 0)","metadata":{"papermill":{"duration":0.092727,"end_time":"2022-05-24T07:43:59.728051","exception":false,"start_time":"2022-05-24T07:43:59.635324","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:58.920472Z","iopub.execute_input":"2022-05-29T11:05:58.921201Z","iopub.status.idle":"2022-05-29T11:05:58.926828Z","shell.execute_reply.started":"2022-05-29T11:05:58.921166Z","shell.execute_reply":"2022-05-29T11:05:58.925868Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 11.2. Calculate Variance","metadata":{"papermill":{"duration":0.0837,"end_time":"2022-05-24T07:43:59.895591","exception":false,"start_time":"2022-05-24T07:43:59.811891","status":"completed"},"tags":[]}},{"cell_type":"code","source":"def get_variance(values):\n    return np.round(np.var(values), 0)","metadata":{"papermill":{"duration":0.102214,"end_time":"2022-05-24T07:44:00.083453","exception":false,"start_time":"2022-05-24T07:43:59.981239","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:58.928531Z","iopub.execute_input":"2022-05-29T11:05:58.92885Z","iopub.status.idle":"2022-05-29T11:05:58.942491Z","shell.execute_reply.started":"2022-05-29T11:05:58.928799Z","shell.execute_reply":"2022-05-29T11:05:58.941774Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 11.3. Calculate Other Metrics","metadata":{"papermill":{"duration":0.083323,"end_time":"2022-05-24T07:44:00.251939","exception":false,"start_time":"2022-05-24T07:44:00.168616","status":"completed"},"tags":[]}},{"cell_type":"code","source":"def get_metrics(target_train, target_test, model_train_predictions, model_test_predictions):\n    training_mse = mean_squared_error(target_train, model_train_predictions)\n    test_mse = mean_squared_error(target_test, model_test_predictions)\n    bias = get_bias(model_test_predictions, target_test)\n    variance = get_variance(model_test_predictions)\n    linear_regression_model = np.polyfit(x_train, y_train, deg=1)\n    \n    return [training_mse,test_mse,bias,variance]","metadata":{"papermill":{"duration":0.115108,"end_time":"2022-05-24T07:44:00.459261","exception":false,"start_time":"2022-05-24T07:44:00.344153","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:58.943469Z","iopub.execute_input":"2022-05-29T11:05:58.943984Z","iopub.status.idle":"2022-05-29T11:05:58.956547Z","shell.execute_reply.started":"2022-05-29T11:05:58.943953Z","shell.execute_reply":"2022-05-29T11:05:58.955636Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"degree=[]\ntraining_mse=[]\ntest_mse=[]\nbias=[]\nvariance=[]","metadata":{"papermill":{"duration":0.093093,"end_time":"2022-05-24T07:44:00.63769","exception":false,"start_time":"2022-05-24T07:44:00.544597","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:58.957856Z","iopub.execute_input":"2022-05-29T11:05:58.958131Z","iopub.status.idle":"2022-05-29T11:05:58.971258Z","shell.execute_reply.started":"2022-05-29T11:05:58.958092Z","shell.execute_reply":"2022-05-29T11:05:58.970329Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 11.4. Checking Metrics","metadata":{"papermill":{"duration":0.084051,"end_time":"2022-05-24T07:44:00.806134","exception":false,"start_time":"2022-05-24T07:44:00.722083","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# Predicting values for the test set\nlinear_model_predictions = np.polyval(linear_regression_model, x_test)\n    \n# Predicting values for the training set\ntraining_linear_model_predictions = np.polyval(linear_regression_model, x_train)\n    \nlinear_training_mse, linear_test_mse, linear_bias, linear_variance = get_metrics(y_train, y_test,training_linear_model_predictions, linear_model_predictions)\n\ndegree.append(1)\ntraining_mse.append(linear_training_mse)\ntest_mse.append(linear_test_mse)\nbias.append(linear_bias)\nvariance.append(linear_variance)\n\n\nprint('Simple linear model')\nprint('- Training MSE %0.f' % linear_training_mse)\nprint('- Test MSE %0.f' % linear_test_mse)\nprint('- Bias %0.f' % linear_bias)\nprint('- Variance %0.f' % linear_variance)","metadata":{"papermill":{"duration":0.103112,"end_time":"2022-05-24T07:44:00.994259","exception":false,"start_time":"2022-05-24T07:44:00.891147","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:58.97266Z","iopub.execute_input":"2022-05-29T11:05:58.972936Z","iopub.status.idle":"2022-05-29T11:05:58.991425Z","shell.execute_reply.started":"2022-05-29T11:05:58.972905Z","shell.execute_reply":"2022-05-29T11:05:58.990539Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 12. Testing with 2nd Degree Polynomial","metadata":{"papermill":{"duration":0.085036,"end_time":"2022-05-24T07:44:01.166317","exception":false,"start_time":"2022-05-24T07:44:01.081281","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"## 12.1. Making Predictions","metadata":{"papermill":{"duration":0.08545,"end_time":"2022-05-24T07:44:01.337228","exception":false,"start_time":"2022-05-24T07:44:01.251778","status":"completed"},"tags":[]}},{"cell_type":"code","source":"#deg=2 for 2nd degree\npolynomial_2nd_model = np.polyfit(x_train, y_train, deg=2)\np_2nd = np.poly1d(polynomial_2nd_model.reshape(1, 3)[0])\nprint('Coefficients %s\\n' % p_2nd)","metadata":{"papermill":{"duration":0.11308,"end_time":"2022-05-24T07:44:01.536487","exception":false,"start_time":"2022-05-24T07:44:01.423407","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:58.992613Z","iopub.execute_input":"2022-05-29T11:05:58.992846Z","iopub.status.idle":"2022-05-29T11:05:59.011652Z","shell.execute_reply.started":"2022-05-29T11:05:58.992817Z","shell.execute_reply":"2022-05-29T11:05:59.010706Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"polynomial_2nd_predictions = np.polyval(polynomial_2nd_model, x_test)\n# Predicting values for the training set\ntraining_polynomial_2nd_predictions = np.polyval(polynomial_2nd_model, x_train)","metadata":{"papermill":{"duration":0.10456,"end_time":"2022-05-24T07:44:01.732806","exception":false,"start_time":"2022-05-24T07:44:01.628246","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:59.012716Z","iopub.execute_input":"2022-05-29T11:05:59.013646Z","iopub.status.idle":"2022-05-29T11:05:59.02583Z","shell.execute_reply.started":"2022-05-29T11:05:59.013598Z","shell.execute_reply":"2022-05-29T11:05:59.025121Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 12.2. Testing metrics","metadata":{"papermill":{"duration":0.101918,"end_time":"2022-05-24T07:44:01.928396","exception":false,"start_time":"2022-05-24T07:44:01.826478","status":"completed"},"tags":[]}},{"cell_type":"code","source":"polynomial_2nd_training_mse, polynomial_2nd_test_mse, polynomial_2nd_bias, polynomial_2nd_variance = get_metrics(y_train, y_test, training_polynomial_2nd_predictions, polynomial_2nd_predictions)\n\ndegree.append(2)\ntraining_mse.append(polynomial_2nd_training_mse)\ntest_mse.append(polynomial_2nd_test_mse)\nbias.append(polynomial_2nd_bias)\nvariance.append(polynomial_2nd_variance)\n\nprint('2nd degree polynomial')\nprint('Training MSE %0.f' % polynomial_2nd_training_mse)\nprint('Test MSE %0.f' % polynomial_2nd_test_mse)\nprint('Bias %0.f' % polynomial_2nd_bias)\nprint('Variance %0.f' % polynomial_2nd_variance)","metadata":{"papermill":{"duration":0.107405,"end_time":"2022-05-24T07:44:02.126852","exception":false,"start_time":"2022-05-24T07:44:02.019447","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:59.026844Z","iopub.execute_input":"2022-05-29T11:05:59.027444Z","iopub.status.idle":"2022-05-29T11:05:59.044154Z","shell.execute_reply.started":"2022-05-29T11:05:59.027412Z","shell.execute_reply":"2022-05-29T11:05:59.043179Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 12.3. Ploting","metadata":{"papermill":{"duration":0.087304,"end_time":"2022-05-24T07:44:02.302527","exception":false,"start_time":"2022-05-24T07:44:02.215223","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# Plot 2nd degree polynomial\nfig, ax = plt.subplots(figsize=(12, 7))\n# removing to and right border\nax.spines['top'].set_visible(False)\nax.spines['right'].set_visible(False)\n# Adding major gridlines\nax.grid(color='grey', linestyle='-', linewidth=0.25, alpha=0.5)\nx_linspace = np.linspace(min(random_x), max(random_x), num=len(polynomial_2nd_predictions))\nmain=ax.scatter(random_x, random_y, color='grey',alpha=0.2,linewidth=6)\nfirst=plt.plot(x_test, linear_model_predictions, color='firebrick', linewidth=1)\nsecond=plt.plot(x_linspace, p_2nd(x_linspace), '-', color='gold', linewidth=3)\n\nplt.legend([first[:1],second[:1]], ['First Degree'])\nplt.legend(second[:1], ['Second Degree']);","metadata":{"papermill":{"duration":0.382272,"end_time":"2022-05-24T07:44:02.775924","exception":false,"start_time":"2022-05-24T07:44:02.393652","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:59.046629Z","iopub.execute_input":"2022-05-29T11:05:59.046892Z","iopub.status.idle":"2022-05-29T11:05:59.3838Z","shell.execute_reply.started":"2022-05-29T11:05:59.046855Z","shell.execute_reply":"2022-05-29T11:05:59.383158Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"- It still underfits.","metadata":{"papermill":{"duration":0.089382,"end_time":"2022-05-24T07:44:02.954985","exception":false,"start_time":"2022-05-24T07:44:02.865603","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"# 13. Testing with 4th Degree Polynomial","metadata":{"papermill":{"duration":0.088162,"end_time":"2022-05-24T07:44:03.133555","exception":false,"start_time":"2022-05-24T07:44:03.045393","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"## 13.1. Making Predictions","metadata":{"papermill":{"duration":0.088195,"end_time":"2022-05-24T07:44:03.310531","exception":false,"start_time":"2022-05-24T07:44:03.222336","status":"completed"},"tags":[]}},{"cell_type":"code","source":"#deg=4 for 4th degree\npolynomial_4thdeg_model = np.polyfit(x_train, y_train, deg=4)\np_4th = np.poly1d(polynomial_4thdeg_model.reshape(1, 5)[0])\nprint('Coefficients %s\\n' % p_4th)","metadata":{"papermill":{"duration":0.098859,"end_time":"2022-05-24T07:44:03.498351","exception":false,"start_time":"2022-05-24T07:44:03.399492","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:59.384906Z","iopub.execute_input":"2022-05-29T11:05:59.385702Z","iopub.status.idle":"2022-05-29T11:05:59.392972Z","shell.execute_reply.started":"2022-05-29T11:05:59.385664Z","shell.execute_reply":"2022-05-29T11:05:59.392114Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"polynomial_4thdeg_predictions = np.polyval(polynomial_4thdeg_model, x_test)\n# Predicting values for the training set\ntraining_polynomial_4thdeg_predictions = np.polyval(polynomial_4thdeg_model, x_train)","metadata":{"papermill":{"duration":0.09712,"end_time":"2022-05-24T07:44:03.684911","exception":false,"start_time":"2022-05-24T07:44:03.587791","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:59.394684Z","iopub.execute_input":"2022-05-29T11:05:59.394939Z","iopub.status.idle":"2022-05-29T11:05:59.407558Z","shell.execute_reply.started":"2022-05-29T11:05:59.394906Z","shell.execute_reply":"2022-05-29T11:05:59.406791Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 13.2. Testing metrics","metadata":{"papermill":{"duration":0.088552,"end_time":"2022-05-24T07:44:03.864118","exception":false,"start_time":"2022-05-24T07:44:03.775566","status":"completed"},"tags":[]}},{"cell_type":"code","source":"polynomial_4thdeg_training_mse, polynomial_4thdeg_test_mse, polynomial_4thdeg_bias, polynomial_4thdeg_variance = get_metrics(y_train, y_test, training_polynomial_4thdeg_predictions, polynomial_4thdeg_predictions)\n\ndegree.append(4)\ntraining_mse.append(polynomial_4thdeg_training_mse)\ntest_mse.append(polynomial_4thdeg_test_mse)\nbias.append(polynomial_4thdeg_bias)\nvariance.append(polynomial_4thdeg_variance)\n\nprint('4th degree polynomial')\nprint('Training MSE %0.f' % polynomial_4thdeg_training_mse)\nprint('Test MSE %0.f' % polynomial_4thdeg_test_mse)\nprint('Bias %0.f' % polynomial_4thdeg_bias)\nprint('Variance %0.f' % polynomial_4thdeg_variance)","metadata":{"papermill":{"duration":0.104386,"end_time":"2022-05-24T07:44:04.05866","exception":false,"start_time":"2022-05-24T07:44:03.954274","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:59.408837Z","iopub.execute_input":"2022-05-29T11:05:59.409208Z","iopub.status.idle":"2022-05-29T11:05:59.423961Z","shell.execute_reply.started":"2022-05-29T11:05:59.409173Z","shell.execute_reply":"2022-05-29T11:05:59.423201Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 13.3. Ploting","metadata":{"papermill":{"duration":0.090846,"end_time":"2022-05-24T07:44:04.238358","exception":false,"start_time":"2022-05-24T07:44:04.147512","status":"completed"},"tags":[]}},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize=(12, 7))\n# removing to and right border\nax.spines['top'].set_visible(False)\nax.spines['right'].set_visible(False)\n# Adding major gridlines\nax.grid(color='grey', linestyle='-', linewidth=0.25, alpha=0.5)\nx_linspace = np.linspace(min(random_x), max(random_x), num=len(polynomial_2nd_predictions))\nmain=ax.scatter(random_x, random_y, color='grey',alpha=0.2,linewidth=6)\nfirst=plt.plot(x_test, linear_model_predictions, color='firebrick', linewidth=1)\nsecond=plt.plot(x_linspace, p_2nd(x_linspace), '-', color='gold', linewidth=1)\nfourth=plt.plot(x_linspace, p_4th(x_linspace), '-', color='green', linewidth=3)\n\nplt.legend(fourth[:1], ['4th Degree']);","metadata":{"papermill":{"duration":0.349459,"end_time":"2022-05-24T07:44:04.677302","exception":false,"start_time":"2022-05-24T07:44:04.327843","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:59.425499Z","iopub.execute_input":"2022-05-29T11:05:59.425849Z","iopub.status.idle":"2022-05-29T11:05:59.754915Z","shell.execute_reply.started":"2022-05-29T11:05:59.425815Z","shell.execute_reply":"2022-05-29T11:05:59.754081Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"- A fair fit now.","metadata":{"papermill":{"duration":0.0904,"end_time":"2022-05-24T07:44:04.859182","exception":false,"start_time":"2022-05-24T07:44:04.768782","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"# 14. Testing with 5th Degree Polynomial (Original)","metadata":{"papermill":{"duration":0.089488,"end_time":"2022-05-24T07:44:05.03988","exception":false,"start_time":"2022-05-24T07:44:04.950392","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"## 14.1. Making Predictions","metadata":{"papermill":{"duration":0.089497,"end_time":"2022-05-24T07:44:05.219391","exception":false,"start_time":"2022-05-24T07:44:05.129894","status":"completed"},"tags":[]}},{"cell_type":"code","source":"polynomial_5thdeg_model = np.polyfit(x_train, y_train, deg=5)\np_5th = np.poly1d(polynomial_5thdeg_model.reshape(1, 6)[0])\npolynomial_5thdeg_predictions = np.polyval(polynomial_5thdeg_model, x_test)\ntraining_polynomial_5thdeg_predictions = np.polyval(polynomial_5thdeg_model, x_train)","metadata":{"papermill":{"duration":0.099626,"end_time":"2022-05-24T07:44:05.408269","exception":false,"start_time":"2022-05-24T07:44:05.308643","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:59.756297Z","iopub.execute_input":"2022-05-29T11:05:59.757304Z","iopub.status.idle":"2022-05-29T11:05:59.764742Z","shell.execute_reply.started":"2022-05-29T11:05:59.757254Z","shell.execute_reply":"2022-05-29T11:05:59.763723Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 14.2. Testing metrics","metadata":{"papermill":{"duration":0.088293,"end_time":"2022-05-24T07:44:05.585417","exception":false,"start_time":"2022-05-24T07:44:05.497124","status":"completed"},"tags":[]}},{"cell_type":"code","source":"polynomial_5thdeg_training_mse, polynomial_5thdeg_test_mse, polynomial_5thdeg_bias, polynomial_5thdeg_variance = get_metrics(y_train, y_test, training_polynomial_5thdeg_predictions, polynomial_5thdeg_predictions)\n\ndegree.append(5)\ntraining_mse.append(polynomial_5thdeg_training_mse)\ntest_mse.append(polynomial_5thdeg_test_mse)\nbias.append(polynomial_5thdeg_bias)\nvariance.append(polynomial_5thdeg_variance)\n\nprint('5th degree polynomial')\nprint('Training MSE %0.f' % polynomial_5thdeg_training_mse)\nprint('Test MSE %0.f' % polynomial_5thdeg_test_mse)\nprint('Bias %0.f' % polynomial_5thdeg_bias)\nprint('Variance %0.f' % polynomial_5thdeg_variance)","metadata":{"papermill":{"duration":0.106547,"end_time":"2022-05-24T07:44:05.784354","exception":false,"start_time":"2022-05-24T07:44:05.677807","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:59.766104Z","iopub.execute_input":"2022-05-29T11:05:59.766428Z","iopub.status.idle":"2022-05-29T11:05:59.78363Z","shell.execute_reply.started":"2022-05-29T11:05:59.766383Z","shell.execute_reply":"2022-05-29T11:05:59.783Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 14.3. Ploting","metadata":{"papermill":{"duration":0.090636,"end_time":"2022-05-24T07:44:05.96799","exception":false,"start_time":"2022-05-24T07:44:05.877354","status":"completed"},"tags":[]}},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize=(12, 7))\n# removing to and right border\nax.spines['top'].set_visible(False)\nax.spines['right'].set_visible(False)\n# Adding major gridlines\nax.grid(color='grey', linestyle='-', linewidth=0.25, alpha=0.1)\nx_linspace = np.linspace(min(random_x), max(random_x), num=len(polynomial_2nd_predictions))\nmain=ax.scatter(random_x, random_y, color='grey',alpha=0.6,linewidth=6)\nfirst=plt.plot(x_test, linear_model_predictions, color='firebrick', linewidth=1)\nsecond=plt.plot(x_linspace, p_2nd(x_linspace), '-', color='gold', linewidth=1)\nfourth=plt.plot(x_linspace, p_4th(x_linspace), '-', color='green', linewidth=1)\nfifth=plt.plot(x_linspace, p_5th(x_linspace), '-', color='red', linewidth=3)\n\nplt.legend(fifth[:1], ['5th Degree']);","metadata":{"papermill":{"duration":0.411379,"end_time":"2022-05-24T07:44:06.472371","exception":false,"start_time":"2022-05-24T07:44:06.060992","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:05:59.784822Z","iopub.execute_input":"2022-05-29T11:05:59.785123Z","iopub.status.idle":"2022-05-29T11:06:00.111681Z","shell.execute_reply.started":"2022-05-29T11:05:59.785054Z","shell.execute_reply":"2022-05-29T11:06:00.110633Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"- A proper fit now.","metadata":{"papermill":{"duration":0.093549,"end_time":"2022-05-24T07:44:06.659247","exception":false,"start_time":"2022-05-24T07:44:06.565698","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"# 15. Testing with 8th Degree Polynomial (Overfit)","metadata":{"papermill":{"duration":0.09148,"end_time":"2022-05-24T07:44:06.84415","exception":false,"start_time":"2022-05-24T07:44:06.75267","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"## 15.1. Making Predictions","metadata":{"papermill":{"duration":0.090958,"end_time":"2022-05-24T07:44:07.027138","exception":false,"start_time":"2022-05-24T07:44:06.93618","status":"completed"},"tags":[]}},{"cell_type":"code","source":"polynomial_8thdeg_model = np.polyfit(x_train, y_train, deg=8)\np_8th = np.poly1d(polynomial_5thdeg_model.reshape(1, 6)[0])\npolynomial_8thdeg_predictions = np.polyval(polynomial_8thdeg_model, x_test)\ntraining_polynomial_8thdeg_predictions = np.polyval(polynomial_8thdeg_model, x_train)","metadata":{"papermill":{"duration":0.101824,"end_time":"2022-05-24T07:44:07.220188","exception":false,"start_time":"2022-05-24T07:44:07.118364","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:06:00.114093Z","iopub.execute_input":"2022-05-29T11:06:00.114362Z","iopub.status.idle":"2022-05-29T11:06:00.120796Z","shell.execute_reply.started":"2022-05-29T11:06:00.114323Z","shell.execute_reply":"2022-05-29T11:06:00.119861Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"polynomial_80thdeg_model = np.polyfit(x_train, y_train, deg=20)\np_80th = np.poly1d(polynomial_80thdeg_model.reshape(1, 21)[0])\npolynomial_80thdeg_predictions = np.polyval(polynomial_80thdeg_model, x_test)\ntraining_polynomial_80thdeg_predictions = np.polyval(polynomial_80thdeg_model, x_train)","metadata":{"papermill":{"duration":0.110973,"end_time":"2022-05-24T07:44:07.42311","exception":false,"start_time":"2022-05-24T07:44:07.312137","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:06:00.121983Z","iopub.execute_input":"2022-05-29T11:06:00.122278Z","iopub.status.idle":"2022-05-29T11:06:00.141176Z","shell.execute_reply.started":"2022-05-29T11:06:00.122242Z","shell.execute_reply":"2022-05-29T11:06:00.139997Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 15.2. Testing metrics","metadata":{"papermill":{"duration":0.09306,"end_time":"2022-05-24T07:44:07.662942","exception":false,"start_time":"2022-05-24T07:44:07.569882","status":"completed"},"tags":[]}},{"cell_type":"code","source":"polynomial_8thdeg_training_mse, polynomial_8thdeg_test_mse, polynomial_8thdeg_bias, polynomial_8thdeg_variance = get_metrics(y_train, y_test, training_polynomial_8thdeg_predictions, polynomial_8thdeg_predictions)\n\ndegree.append(8)\ntraining_mse.append(polynomial_8thdeg_training_mse)\ntest_mse.append(polynomial_8thdeg_test_mse)\nbias.append(polynomial_8thdeg_bias)\nvariance.append(polynomial_8thdeg_variance)\n\nprint('8th degree polynomial')\nprint('Training MSE %0.f' % polynomial_8thdeg_training_mse)\nprint('Test MSE %0.f' % polynomial_8thdeg_test_mse)\nprint('Bias %0.f' % polynomial_8thdeg_bias)\nprint('Variance %0.f' % polynomial_8thdeg_variance)","metadata":{"papermill":{"duration":0.108829,"end_time":"2022-05-24T07:44:07.864865","exception":false,"start_time":"2022-05-24T07:44:07.756036","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:06:00.142994Z","iopub.execute_input":"2022-05-29T11:06:00.143923Z","iopub.status.idle":"2022-05-29T11:06:00.15956Z","shell.execute_reply.started":"2022-05-29T11:06:00.143864Z","shell.execute_reply":"2022-05-29T11:06:00.158555Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"polynomial_80thdeg_training_mse, polynomial_80thdeg_test_mse, polynomial_80thdeg_bias, polynomial_80thdeg_variance = get_metrics(y_train, y_test, training_polynomial_80thdeg_predictions, polynomial_80thdeg_predictions)\n\ndegree.append(20)\ntraining_mse.append(polynomial_80thdeg_training_mse)\ntest_mse.append(polynomial_80thdeg_test_mse)\nbias.append(polynomial_80thdeg_bias)\nvariance.append(polynomial_80thdeg_variance)\n\nprint('80th degree polynomial')\nprint('Training MSE %0.f' % polynomial_80thdeg_training_mse)\nprint('Test MSE %0.f' % polynomial_80thdeg_test_mse)\nprint('Bias %0.f' % polynomial_80thdeg_bias)\nprint('Variance %0.f' % polynomial_80thdeg_variance)","metadata":{"papermill":{"duration":0.107547,"end_time":"2022-05-24T07:44:08.06802","exception":false,"start_time":"2022-05-24T07:44:07.960473","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:06:00.161647Z","iopub.execute_input":"2022-05-29T11:06:00.162351Z","iopub.status.idle":"2022-05-29T11:06:00.17608Z","shell.execute_reply.started":"2022-05-29T11:06:00.162168Z","shell.execute_reply":"2022-05-29T11:06:00.175139Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 15.3. Ploting","metadata":{"papermill":{"duration":0.098653,"end_time":"2022-05-24T07:44:08.260387","exception":false,"start_time":"2022-05-24T07:44:08.161734","status":"completed"},"tags":[]}},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize=(12, 7))\n# removing to and right border\nax.spines['top'].set_visible(False)\nax.spines['right'].set_visible(False)\n# Adding major gridlines\nax.grid(color='grey', linestyle='-', linewidth=0.25, alpha=0.5)\nx_linspace = np.linspace(min(random_x), max(random_x), num=len(polynomial_2nd_predictions))\nmain=ax.scatter(random_x, random_y, color='grey',alpha=0.2,linewidth=6)\nfirst=plt.plot(x_test, linear_model_predictions, color='firebrick', linewidth=1)\nsecond=plt.plot(x_linspace, p_2nd(x_linspace), '-', color='gold', linewidth=1)\nfourth=plt.plot(x_linspace, p_4th(x_linspace), '-', color='green', linewidth=1)\nfifth=plt.plot(x_linspace, p_5th(x_linspace), '-', color='red', linewidth=1)\neighth=plt.plot(x_linspace, p_8th(x_linspace), '-', color='blue', linewidth=3)\n\nplt.legend(fourth[:1], ['8th Degree']);","metadata":{"papermill":{"duration":0.398279,"end_time":"2022-05-24T07:44:08.7526","exception":false,"start_time":"2022-05-24T07:44:08.354321","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:06:00.178052Z","iopub.execute_input":"2022-05-29T11:06:00.17863Z","iopub.status.idle":"2022-05-29T11:06:00.490799Z","shell.execute_reply.started":"2022-05-29T11:06:00.178574Z","shell.execute_reply":"2022-05-29T11:06:00.490163Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize=(12, 7))\n# removing to and right border\nax.spines['top'].set_visible(False)\nax.spines['right'].set_visible(False)\n# Adding major gridlines\nax.grid(color='grey', linestyle='-', linewidth=0.25, alpha=0.5)\nx_linspace = np.linspace(min(random_x), max(random_x), num=len(polynomial_2nd_predictions))\nmain=ax.scatter(random_x, random_y, color='grey',alpha=0.2,linewidth=6)\nfirst=plt.plot(x_test, linear_model_predictions, color='firebrick', linewidth=1)\nsecond=plt.plot(x_linspace, p_2nd(x_linspace), '-', color='gold', linewidth=1)\nfourth=plt.plot(x_linspace, p_4th(x_linspace), '-', color='green', linewidth=1)\nfifth=plt.plot(x_linspace, p_5th(x_linspace), '-', color='red', linewidth=1)\neighth=plt.plot(x_linspace, p_8th(x_linspace), '-', color='blue', linewidth=1)\neighthy=plt.plot(x_linspace, p_80th(x_linspace), '-', color='purple', linewidth=3)\n\nplt.legend(fourth[:1], ['20th Degree']);","metadata":{"papermill":{"duration":0.406163,"end_time":"2022-05-24T07:44:09.25519","exception":false,"start_time":"2022-05-24T07:44:08.849027","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:06:00.492908Z","iopub.execute_input":"2022-05-29T11:06:00.493624Z","iopub.status.idle":"2022-05-29T11:06:00.809231Z","shell.execute_reply.started":"2022-05-29T11:06:00.493579Z","shell.execute_reply":"2022-05-29T11:06:00.808472Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"- started to overfit.","metadata":{"papermill":{"duration":0.096229,"end_time":"2022-05-24T07:44:09.448721","exception":false,"start_time":"2022-05-24T07:44:09.352492","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"# 16. Ploting Metrics","metadata":{"papermill":{"duration":0.097482,"end_time":"2022-05-24T07:44:09.642991","exception":false,"start_time":"2022-05-24T07:44:09.545509","status":"completed"},"tags":[]}},{"cell_type":"code","source":"lst = [degree,training_mse,test_mse,bias,variance]\nmetrics_df = pd.DataFrame(lst)\nmetrics_df=metrics_df.T\nmetrics_df.rename(columns = {0:\"degree\",1:\"training_mse\",2:\"test_mse\",3:\"bias\",4:\"variance\"}, inplace = True)\nmetrics_df","metadata":{"papermill":{"duration":0.121775,"end_time":"2022-05-24T07:44:09.862693","exception":false,"start_time":"2022-05-24T07:44:09.740918","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:06:00.810611Z","iopub.execute_input":"2022-05-29T11:06:00.811015Z","iopub.status.idle":"2022-05-29T11:06:00.829255Z","shell.execute_reply.started":"2022-05-29T11:06:00.81096Z","shell.execute_reply":"2022-05-29T11:06:00.828167Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"metrics_df.describe()","metadata":{"papermill":{"duration":0.132038,"end_time":"2022-05-24T07:44:10.093685","exception":false,"start_time":"2022-05-24T07:44:09.961647","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:06:00.831016Z","iopub.execute_input":"2022-05-29T11:06:00.831401Z","iopub.status.idle":"2022-05-29T11:06:00.863686Z","shell.execute_reply.started":"2022-05-29T11:06:00.831352Z","shell.execute_reply":"2022-05-29T11:06:00.862811Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 16.1. Plotting MSEs","metadata":{"papermill":{"duration":0.097852,"end_time":"2022-05-24T07:44:10.290424","exception":false,"start_time":"2022-05-24T07:44:10.192572","status":"completed"},"tags":[]}},{"cell_type":"code","source":"plt.figure(figsize=(10,10))\ntrace1 = go.Scatter(x=metrics_df.degree,\n                    y=metrics_df.training_mse,\n                    name = \"Training\",\n                    line = dict(color = 'green'),\n                    opacity = 0.9,\n                    marker=dict(\n                        color='white',\n                        size=10,\n                        line=dict(\n                            width=5\n                        )))\n\ntrace2 = go.Scatter(x=metrics_df.degree,\n                    y=metrics_df.test_mse,\n                    name = \"Test\",\n                    line = dict(color = 'red'),\n                    opacity = 0.9,\n                    marker=dict(\n                        color='white',\n                        size=10,\n                        line=dict(\n                            width=5\n                        )))\n\nlayout2 = dict(title='Mean Squared Error',)\n\nfig2 = dict(data=[trace1, trace2], layout=layout2)\n\niplot(fig2)","metadata":{"_kg_hide-input":true,"papermill":{"duration":1.049387,"end_time":"2022-05-24T07:44:11.441732","exception":false,"start_time":"2022-05-24T07:44:10.392345","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:06:00.864952Z","iopub.execute_input":"2022-05-29T11:06:00.865377Z","iopub.status.idle":"2022-05-29T11:06:01.119603Z","shell.execute_reply.started":"2022-05-29T11:06:00.865342Z","shell.execute_reply":"2022-05-29T11:06:01.119008Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 16.2. Potting Bias","metadata":{"papermill":{"duration":0.10933,"end_time":"2022-05-24T07:44:11.658588","exception":false,"start_time":"2022-05-24T07:44:11.549258","status":"completed"},"tags":[]}},{"cell_type":"code","source":"plt.figure(figsize=(10,10))\nBias = go.Scatter(x=metrics_df.degree,\n                    y=metrics_df.bias,\n                    name = \"Bias\",\n                    line = dict(color = 'darkorange'),\n                    opacity = 1,\n                    marker=dict(\n                        color='white',\n                        size=10,\n                        line=dict(\n                            width=12\n                        )))\n\nlayout2 = dict(title='Bias',)\n\nfig = dict(data=[Bias], layout=layout2)\n\niplot(fig)","metadata":{"_kg_hide-input":true,"papermill":{"duration":0.147645,"end_time":"2022-05-24T07:44:11.910795","exception":false,"start_time":"2022-05-24T07:44:11.76315","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:06:01.12081Z","iopub.execute_input":"2022-05-29T11:06:01.121553Z","iopub.status.idle":"2022-05-29T11:06:01.163257Z","shell.execute_reply.started":"2022-05-29T11:06:01.121487Z","shell.execute_reply":"2022-05-29T11:06:01.162281Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 16.2. Potting Variance","metadata":{"papermill":{"duration":0.111591,"end_time":"2022-05-24T07:44:12.132943","exception":false,"start_time":"2022-05-24T07:44:12.021352","status":"completed"},"tags":[]}},{"cell_type":"code","source":"plt.figure(figsize=(10,10))\nVariance = go.Scatter(x=metrics_df.degree,\n                    y=metrics_df.variance,\n                    name = \"Variance\",\n                    line = dict(color = 'indigo'),\n                    opacity = 1,\n                    marker=dict(\n                        color='white',\n                        size=10,\n                        line=dict(\n                            width=12\n                        )))\n\nlayout2 = dict(title='Variance',)\n\nfig = dict(data=[Variance], layout=layout2)\n\niplot(fig)","metadata":{"_kg_hide-input":true,"papermill":{"duration":0.158044,"end_time":"2022-05-24T07:44:12.400851","exception":false,"start_time":"2022-05-24T07:44:12.242807","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:06:01.165106Z","iopub.execute_input":"2022-05-29T11:06:01.165446Z","iopub.status.idle":"2022-05-29T11:06:01.207522Z","shell.execute_reply.started":"2022-05-29T11:06:01.165401Z","shell.execute_reply":"2022-05-29T11:06:01.206737Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 16.2. Potting Bias - Variance","metadata":{"papermill":{"duration":0.118861,"end_time":"2022-05-24T07:44:12.639313","exception":false,"start_time":"2022-05-24T07:44:12.520452","status":"completed"},"tags":[]}},{"cell_type":"code","source":"layout = dict(title='Bias - Variance',)\nfig = dict(data=[Bias, Variance], layout=layout)\niplot(fig)","metadata":{"papermill":{"duration":0.161728,"end_time":"2022-05-24T07:44:12.91929","exception":false,"start_time":"2022-05-24T07:44:12.757562","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2022-05-29T11:06:01.208772Z","iopub.execute_input":"2022-05-29T11:06:01.209639Z","iopub.status.idle":"2022-05-29T11:06:01.245893Z","shell.execute_reply.started":"2022-05-29T11:06:01.209591Z","shell.execute_reply":"2022-05-29T11:06:01.244991Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_df.describe()","metadata":{"execution":{"iopub.status.busy":"2022-11-03T23:42:52.888892Z","iopub.execute_input":"2022-11-03T23:42:52.889210Z","iopub.status.idle":"2022-11-03T23:42:54.546059Z","shell.execute_reply.started":"2022-11-03T23:42:52.889181Z","shell.execute_reply":"2022-11-03T23:42:54.545305Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"- data seems quite stable!","metadata":{}},{"cell_type":"markdown","source":"# 17. Reference\n- [Gentle Introduction to the Bias-Variance Trade-Off in Machine Learning](https://machinelearningmastery.com/gentle-introduction-to-the-bias-variance-trade-off-in-machine-learning/#:~:text=Bias%20is%20the%20simplifying%20assumptions,the%20bias%20and%20the%20variance)\n- [Bias-Variance tradeoff in Machine Learning models](https://towardsdatascience.com/bias-variance-tradeoff-in-machine-learning-models-a-practical-example-cf02fb95b15d)\n- [Understanding the Bias-Variance Tradeoff](https://towardsdatascience.com/understanding-the-bias-variance-tradeoff-165e6942b229)\n- [What Bias-Variance Bulls-Eye Diagram Really Represents](https://towardsdatascience.com/what-bias-variance-bulls-eye-diagram-really-represent-ff6fb9670993)\n- [What Is the Difference Between Bias and Variance?](https://www.mastersindatascience.org/learning/difference-between-bias-and-variance/)","metadata":{"papermill":{"duration":0.12527,"end_time":"2022-05-24T07:44:13.168411","exception":false,"start_time":"2022-05-24T07:44:13.043141","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"# 18. Cheatsheets\n[![BVT-CS.png](https://i.postimg.cc/6pmyHhCr/BVT-CS.png)](https://postimg.cc/5X84yL7y)","metadata":{}},{"cell_type":"markdown","source":"# Learn, Share, Support","metadata":{"papermill":{"duration":0.124052,"end_time":"2022-05-24T07:44:13.415648","exception":false,"start_time":"2022-05-24T07:44:13.291596","status":"completed"},"tags":[]}}]}