{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nimport os\nprint(os.listdir(\"../input\"))\n\ndata=pd.read_csv('../input/train.csv')\n\n# Any results you write to the current directory are saved as output.","execution_count":3,"outputs":[{"output_type":"stream","text":"['test.csv', 'train.csv', 'sample_submission.csv', 'embeddings']\n","name":"stdout"}]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"data.head()\nprint(data.shape)","execution_count":7,"outputs":[{"output_type":"stream","text":"(1306122, 3)\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"data[data['target']==1].head()","execution_count":8,"outputs":[{"output_type":"execute_result","execution_count":8,"data":{"text/plain":"                      qid  ...   target\n22   0000e91571b60c2fb487  ...        1\n30   00013ceca3f624b09f42  ...        1\n110  0004a7fcb2bf73076489  ...        1\n114  00052793eaa287aff1e1  ...        1\n115  000537213b01fd77b58a  ...        1\n\n[5 rows x 3 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>qid</th>\n      <th>question_text</th>\n      <th>target</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>22</th>\n      <td>0000e91571b60c2fb487</td>\n      <td>Has the United States become the largest dicta...</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>00013ceca3f624b09f42</td>\n      <td>Which babies are more sweeter to their parents...</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>110</th>\n      <td>0004a7fcb2bf73076489</td>\n      <td>If blacks support school choice and mandatory ...</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>114</th>\n      <td>00052793eaa287aff1e1</td>\n      <td>I am gay boy and I love my cousin (boy). He is...</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>115</th>\n      <td>000537213b01fd77b58a</td>\n      <td>Which races have the smallest penis?</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"len(data[data['target']==1])/len(data['target'])","execution_count":21,"outputs":[{"output_type":"execute_result","execution_count":21,"data":{"text/plain":"0.06187017751787352"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"data['target'].value_counts()","execution_count":20,"outputs":[{"output_type":"execute_result","execution_count":20,"data":{"text/plain":"0    1225312\n1      80810\nName: target, dtype: int64"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from wordcloud import WordCloud\nimport matplotlib.pyplot as plt\ninsincere_rows=data[data['target']==1]\nwc=WordCloud(background_color='white').generate(' '.join(insincere_rows['question_text']))\n\nplt.imshow(wc)","execution_count":19,"outputs":[{"output_type":"execute_result","execution_count":19,"data":{"text/plain":"<matplotlib.image.AxesImage at 0x7f01872074a8>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.model_selection import train_test_split\n\ntrain,validate=train_test_split(data,test_size=0.3,random_state=1)\n\ntrain.shape,validate.shape","execution_count":23,"outputs":[{"output_type":"execute_result","execution_count":23,"data":{"text/plain":"((914285, 3), (391837, 3))"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"import nltk\ndef clean_sentence(doc,stopwords,stemmer):\n    words=doc.split(' ')\n    words_clean=[stemmer.stem(word) for word in words if word not in stopwords]\n    return ' '.join(words_clean)\ndef clean_documents(docs_raw):\n    stopwords=nltk.corpus.stopwords.words('english')\n    stemmer=nltk.stem.PorterStemmer()\n    docs=docs_raw.str.lower().str.replace('[^a-z ]','')\n    docs_clean=docs.apply(lambda doc:clean_sentence(doc,stopwords,stemmer))\n    return docs_clean\ntrain_docs_clean=clean_documents(train['question_text'])\ntrain_docs_clean.head()","execution_count":27,"outputs":[{"output_type":"execute_result","execution_count":27,"data":{"text/plain":"635414          inhand salari rd prc freshli join mt cil\n906079                             one take yolo serious\n99492                                  best club nairobi\n973656    wake donald trump clock tick  hour return bodi\n397612                              made elon musk smart\nName: question_text, dtype: object"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.feature_extraction.text import CountVectorizer\n\nvectorizer=CountVectorizer(min_df=10).fit(train_docs_clean)\n\ndtm=vectorizer.transform(train_docs_clean)","execution_count":29,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"dtm.shape","execution_count":30,"outputs":[{"output_type":"execute_result","execution_count":30,"data":{"text/plain":"(914285, 19550)"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"#pd.DataFrame(dtm.array())   ------>Memory Error","execution_count":31,"outputs":[{"output_type":"error","ename":"AttributeError","evalue":"array not found","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)","\u001b[0;32m<ipython-input-31-5c1b29c5e426>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/opt/conda/lib/python3.6/site-packages/scipy/sparse/base.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, attr)\u001b[0m\n\u001b[1;32m    684\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetnnz\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    685\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 686\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mattr\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\" not found\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    687\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    688\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mAttributeError\u001b[0m: array not found"]}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.tree import DecisionTreeClassifier\n\nmodel_df=DecisionTreeClassifier(max_depth=10).fit(dtm,train['target'])","execution_count":33,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"validate_docs_clean = clean_documents(validate['question_text'])\ndtm_validate= vectorizer.transform(validate_docs_clean)\ndtm_validate","execution_count":35,"outputs":[{"output_type":"execute_result","execution_count":35,"data":{"text/plain":"<391837x19550 sparse matrix of type '<class 'numpy.int64'>'\n\twith 2313528 stored elements in Compressed Sparse Row format>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"predict=model_df.predict(dtm_validate)","execution_count":38,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.metrics import accuracy_score,classification_report,confusion_matrix,f1_score","execution_count":36,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"f1_score(validate['target'],predict)","execution_count":39,"outputs":[{"output_type":"execute_result","execution_count":39,"data":{"text/plain":"0.2613359657782165"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.naive_bayes import MultinomialNB\n\nnb=MultinomialNB().fit(dtm,train['target'])\n\nvalidate_pred=nb.predict(dtm_validate)\n\nf1_score(validate['target'],validate_pred)","execution_count":40,"outputs":[{"output_type":"execute_result","execution_count":40,"data":{"text/plain":"0.5425968470252713"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"#from sklearn.model_selection import GridSearchCV","execution_count":42,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test=pd.read_csv('../input/test.csv')\n\ndocs_clean=clean_documents(test['question_text'])\n\ndtm_test=vectorizer.transform(docs_clean)\n\ndtm_test","execution_count":43,"outputs":[{"output_type":"execute_result","execution_count":43,"data":{"text/plain":"<375806x19550 sparse matrix of type '<class 'numpy.int64'>'\n\twith 2220720 stored elements in Compressed Sparse Row format>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_pred=nb.predict(dtm_test)\n\ntest_pred","execution_count":45,"outputs":[{"output_type":"execute_result","execution_count":45,"data":{"text/plain":"array([1, 0, 0, ..., 0, 0, 0])"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"sam_sub=pd.read_csv('../input/sample_submission.csv')\n\n\nsubmission=pd.DataFrame({'qid':test['qid'],'prediction':test_pred})\n\n\nsubmission[['qid','prediction']].to_csv('submission.csv',index=False)","execution_count":47,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.4","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}