{"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":"# 1. Mô tả bài toán \nQuora là một nền tảng cho phép mọi người học hỏi lẫn nhau. Trên Quora, mọi người có thể đặt câu hỏi để những người khác tương tác, đưa ra những câu trả lời chất lượng. Bài toán đặt ra là làm thế nào để loại bỏ những câu hỏi thiếu thành thật (insincere question) - những câu hỏi dựa trên những định kiến sai lầm hoặc có ý định đưa ra một tuyên bố hơn là tìm kiếm những câu trả lời hữu ích","metadata":{}},{"cell_type":"markdown","source":"Các câu hỏi insincere sẽ được đánh dấu là 1, và các câu hỏi còn lại được đánh dấu là 0","metadata":{}},{"cell_type":"markdown","source":"Metrics được sử dụng để đánh gía mô hình ở đây cho các file submisson là điểm F1","metadata":{}},{"cell_type":"markdown","source":"### Các thư viện được sử dụng","metadata":{}},{"cell_type":"code","source":"import re\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom collections import Counter\nfrom wordcloud import STOPWORDS\nimport seaborn as sb\nfrom sklearn.model_selection import StratifiedKFold\nfrom keras.preprocessing.text import Tokenizer\nfrom keras.preprocessing.sequence import pad_sequences\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader\nimport torch\n","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:09.507784Z","iopub.execute_input":"2022-01-08T10:07:09.508131Z","iopub.status.idle":"2022-01-08T10:07:16.190209Z","shell.execute_reply.started":"2022-01-08T10:07:09.508047Z","shell.execute_reply":"2022-01-08T10:07:16.189527Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"!pip install nltk==3.4 \nimport nltk","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:16.191789Z","iopub.execute_input":"2022-01-08T10:07:16.192041Z","iopub.status.idle":"2022-01-08T10:07:30.037482Z","shell.execute_reply.started":"2022-01-08T10:07:16.192005Z","shell.execute_reply":"2022-01-08T10:07:30.036638Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 2. Phân tích dữ liệu\n## 2.1 Tổng quan về dữ liệu","metadata":{}},{"cell_type":"code","source":"# Load dữ liệu huấn luyện và dữ liệu test bằng hàm read_csv từ thư viện pandas\ntrain_df = pd.read_csv('../input/quora-insincere-questions-classification/train.csv')\ntest_df = pd.read_csv('../input/quora-insincere-questions-classification/test.csv')\n\nprint('Số lượng điểm dữ liệu ở trong tập huấn luyện:', train_df.shape[0])\nprint('Số lượng điểm dữ liệu ở trong tập test:', test_df.shape[0])\n","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:30.039003Z","iopub.execute_input":"2022-01-08T10:07:30.039274Z","iopub.status.idle":"2022-01-08T10:07:35.522559Z","shell.execute_reply.started":"2022-01-08T10:07:30.039236Z","shell.execute_reply":"2022-01-08T10:07:35.521020Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Xem dữ liệu huấn luyện\ntrain_df.head(10)","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:35.525253Z","iopub.execute_input":"2022-01-08T10:07:35.525510Z","iopub.status.idle":"2022-01-08T10:07:35.545081Z","shell.execute_reply.started":"2022-01-08T10:07:35.525461Z","shell.execute_reply":"2022-01-08T10:07:35.544417Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Bộ dữ liệu huấn luyện gồm 3 cột: qid, question_text (nội dung câu hỏi) và target (là giá trị nhị phân 0,1, với 0 là sincere question, 1 là insincere question)","metadata":{}},{"cell_type":"code","source":"# kiểm tra các điểm dữ liệu trong dữ liệu huấn luyện có giá trị null nào không\nprint('Số giá trị null ở cột qid, question_text, target:', train_df['qid'].isnull().sum(),',',\n                                                            train_df['question_text'].isnull().sum(),',',\n                                                            train_df['target'].isnull().sum())\n","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:35.546155Z","iopub.execute_input":"2022-01-08T10:07:35.546749Z","iopub.status.idle":"2022-01-08T10:07:35.806627Z","shell.execute_reply.started":"2022-01-08T10:07:35.546713Z","shell.execute_reply":"2022-01-08T10:07:35.805947Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Xem các sincere question ở trong dữ liệu huấn luyện\ntrain_df[train_df['target']==0].head(5)","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:35.807725Z","iopub.execute_input":"2022-01-08T10:07:35.807970Z","iopub.status.idle":"2022-01-08T10:07:35.886058Z","shell.execute_reply.started":"2022-01-08T10:07:35.807935Z","shell.execute_reply":"2022-01-08T10:07:35.885235Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#Xem các insincere question ở trong dữ liệu huấn luyện\ntrain_df[train_df['target']==1].head(5)","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:35.887366Z","iopub.execute_input":"2022-01-08T10:07:35.887765Z","iopub.status.idle":"2022-01-08T10:07:35.912743Z","shell.execute_reply.started":"2022-01-08T10:07:35.887727Z","shell.execute_reply":"2022-01-08T10:07:35.912046Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#Xem dữ liệu test\ntest_df.head(10)","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:35.913856Z","iopub.execute_input":"2022-01-08T10:07:35.914223Z","iopub.status.idle":"2022-01-08T10:07:35.923143Z","shell.execute_reply.started":"2022-01-08T10:07:35.914186Z","shell.execute_reply":"2022-01-08T10:07:35.922224Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 2.2. Trực quan hóa dữ liệu","metadata":{}},{"cell_type":"markdown","source":"## 2.2.1 Trực quan hóa dữ liệu trong tập huấn luyện","metadata":{}},{"cell_type":"markdown","source":"#### Số lượng các câu hỏi ở mỗi loại trong tập training","metadata":{}},{"cell_type":"code","source":"train_df['target'].value_counts() # Với 0 là sincere question, 1 là insincere question","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:35.924339Z","iopub.execute_input":"2022-01-08T10:07:35.924794Z","iopub.status.idle":"2022-01-08T10:07:35.942553Z","shell.execute_reply.started":"2022-01-08T10:07:35.924756Z","shell.execute_reply":"2022-01-08T10:07:35.941668Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#### Trực quan hóa số lượng các câu hỏi thông qua bar chart và pie chart","metadata":{}},{"cell_type":"code","source":"# Biểu đồ số lượng các câu hỏi\nplt.subplot(1, 2, 1)\ntrain_df.groupby('target')['qid'].count().plot.bar()\nplt.grid(True)\nplt.title('Question Count')\nplt.subplots_adjust(right=1.9)\n\n# Biểu đồ phân phối các câu hỏi \nplt.subplot(1, 2, 2)\nvalues = [train_df[train_df['target']==0].shape[0], train_df[train_df['target']==1].shape[0]]\nlabels = ['Sincere questions', 'Insincere questions']\n\nplt.pie(values, labels=labels, autopct='%1.1f%%', shadow=True)\nplt.title('Question Distribution')\nplt.tight_layout()\nplt.subplots_adjust(right=1.9)\n\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:35.946586Z","iopub.execute_input":"2022-01-08T10:07:35.946813Z","iopub.status.idle":"2022-01-08T10:07:36.927324Z","shell.execute_reply.started":"2022-01-08T10:07:35.946789Z","shell.execute_reply":"2022-01-08T10:07:36.923806Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Bộ dữ liệu huấn luyện có sự mất cân bằng khi 93,8% () là các câu hỏi sincere, 6,2% còn lại là insincere question. Ta cần có giải pháp cân bằng lại dữ liệu trong tập training","metadata":{}},{"cell_type":"markdown","source":"### 2.2.1.1. Các từ có tần suất xuất hiện nhiều nhất trong sincere và insincere questions","metadata":{}},{"cell_type":"markdown","source":"\nTa sử dụng phương pháp N-grams để tìm các từ/ cụm từ có tần suất được sử dụng nhiều nhất trong từng loại câu hỏi. \n\nỞ đây, ta sử dụng 1-grams (unigrams) và 2-grams (bigrams). \nVí dụ: \"hôm nay trời đẹp\". \n* unigrams: \"hôm\",\"nay\",\"trời\",\"đẹp\"\n* bigrams: \"hôm nay\", \"nay trời\", \"trời đẹp\"","metadata":{}},{"cell_type":"code","source":"def pltTopWord(data, title, bar_color, numberOfWordsInTop):\n    \n    top_words = Counter(data).most_common(numberOfWordsInTop) # 25 từ xuất hiện nhiều nhất\n\n    df_top = pd.DataFrame(top_words, columns=['word', 'count']).sort_values('count')\n\n    plt.barh(df_top['word'].values, df_top['count'].values, orientation='horizontal', color=bar_color)\n    plt.title(f'Top words in {title}')","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:36.928691Z","iopub.execute_input":"2022-01-08T10:07:36.928958Z","iopub.status.idle":"2022-01-08T10:07:36.934406Z","shell.execute_reply.started":"2022-01-08T10:07:36.928923Z","shell.execute_reply":"2022-01-08T10:07:36.933491Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"","metadata":{}},{"cell_type":"code","source":"def get_unigrams(data):\n    unigrams = []\n    for sent in data:\n        unigrams.extend([w for w in sent.lower().split() if w not in STOPWORDS]) # không lấy các từ stopword\n    return unigrams\n\ndef get_bigrams(data):\n    bigrams = []\n    for question in data:\n        question = [w for w in question.lower().split() if w not in STOPWORDS] # không lấy các từ stopword\n        if not question: \n            continue # tránh việc mảng question rỗng gây ra lỗi khi dùng nltk.bigrmas\n        bi = [b for b in nltk.bigrams(question)]\n        bi = [' '.join(w) for w in bi]\n        bigrams.extend(bi)\n    return bigrams","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:36.935829Z","iopub.execute_input":"2022-01-08T10:07:36.936344Z","iopub.status.idle":"2022-01-08T10:07:36.945479Z","shell.execute_reply.started":"2022-01-08T10:07:36.936266Z","shell.execute_reply":"2022-01-08T10:07:36.944768Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"unigrams_sincere  = get_unigrams(train_df[train_df['target']==0]['question_text'])\nunigrams_insincere = get_unigrams(train_df[train_df['target']==1]['question_text'])\n\nplt.subplot(1, 2, 1)\npltTopWord(unigrams_sincere, 'Sincere questions: Unigrams', 'blue',25)\n\n\nplt.subplot(1, 2, 2)\npltTopWord(unigrams_insincere, 'Insincere questions: Unigrams', 'red',25)\n\nplt.subplots_adjust(right=3.0)\nplt.subplots_adjust(top=2.0)\nplt.show()\n","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:36.946951Z","iopub.execute_input":"2022-01-08T10:07:36.947313Z","iopub.status.idle":"2022-01-08T10:07:43.003485Z","shell.execute_reply.started":"2022-01-08T10:07:36.947278Z","shell.execute_reply":"2022-01-08T10:07:43.002811Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"bigrams_sincere = get_bigrams(train_df[train_df['target']==0]['question_text'])\nbigrams_insincere = get_bigrams(train_df[train_df['target']==1]['question_text'])\n\nplt.subplot(1, 2, 1)\npltTopWord(bigrams_sincere, 'Sincere questions: Bigrams', 'blue',25)\n\nplt.subplot(1, 2, 2)\npltTopWord(bigrams_insincere, 'Insincere questions: Bigrams', 'red',25)\n\nplt.subplots_adjust(right=3.0)\nplt.subplots_adjust(top=2.0)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:43.004647Z","iopub.execute_input":"2022-01-08T10:07:43.005080Z","iopub.status.idle":"2022-01-08T10:07:58.953917Z","shell.execute_reply.started":"2022-01-08T10:07:43.005035Z","shell.execute_reply":"2022-01-08T10:07:58.953201Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Sau khi loại bỏ các stopwords, với các sincere question, các từ xuất hiện nhiều nhất thường là những từ mang nghĩa tích cực như: best, possible, people, etc. Với các insincere question, các từ xuất hiện nhiều nhất thường là: donald trump, black, indian.","metadata":{}},{"cell_type":"markdown","source":"### 2.2.1.2 Một vài đặc trưng cơ bản ","metadata":{}},{"cell_type":"markdown","source":"#### Bổ sung các đặc trưng ","metadata":{}},{"cell_type":"markdown","source":"Ta sẽ thêm một vài đặc trưng cơ bản của câu hỏi vào trong tập training:\n* Độ dài của câu\n* Số lượng từ \n* Số lượng từ không trùng nhau\n* Số lượng các stopwords\n* Số lượng ký tự đặc biệt (ở đây, các ký tự ngoài chữ,số, dấu space, ta coi là các ký tự đặc biệt)","metadata":{}},{"cell_type":"code","source":"special_character_list = []\ndef count_special_character_in(text):\n    count = 0\n    for i in range(0, len(text)):\n        if((text[i].isalpha())  or text[i] ==' '):\n            continue\n        elif(text[i].isdigit()):\n            continue   \n        else:\n            special_character_list.extend(text[i])\n            count+=1\n    return count\n\n\n\n# Độ dài của câu\ntrain_df['question_length'] = train_df['question_text'].apply(lambda ques: len(str(ques)))\n\n# Số lượng từ của câu\ntrain_df['number_of_words'] = train_df['question_text'].apply(lambda ques: len(str(ques).split()))\nmax_word = train_df['number_of_words'].max()\nprint(max_word)\n\n#Số lượng từ không trùng nhau của câu\ntrain_df['number_of_unique_words'] = train_df['question_text'].apply(lambda ques: len(set(str(ques).split())))\n\n#Số lượng các stopwords\ntrain_df['number_of_stopwords'] = train_df['question_text'].apply(lambda ques: len([w for w in str(ques).lower().split() if w in STOPWORDS]))\n\n#Số lượng các ký tự đặc biệt\ntrain_df['number_special'] = train_df['question_text'].apply(lambda ques: count_special_character_in(ques))\n\nspecial_character_list = set(special_character_list)\nprint(list(set(special_character_list)))\n\ntrain_df.head(5)\n","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:07:58.955013Z","iopub.execute_input":"2022-01-08T10:07:58.955387Z","iopub.status.idle":"2022-01-08T10:08:19.622465Z","shell.execute_reply.started":"2022-01-08T10:07:58.955350Z","shell.execute_reply":"2022-01-08T10:08:19.621725Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#### Phân tích các đặc trưng","metadata":{}},{"cell_type":"markdown","source":"Ta sử dụng box plot để phân tích các đặc trưng. Box plot là một dạng biểu đồ thể hiện phân phối dữ liệu các thuộc tính thông qua các tứ phân vị. Box plot thể hiện các phân phối dữ liệu, giúp ta biết độ phân bố của các điểm dữ liệu như thế nào, dữ liệu có phân bố rộng hay hẹp, giá trị lớn nhất và các điểm ngoại lệ.\n\n<img src=\"https://miro.medium.com/max/1400/1*2c21SkzJMf3frPXPAR_gZA.png\">\n\nBiểu đồ Boxplot thể hiện 6 thông số:\n* Median: Trung vị của tập dữ liệu, tức là giá trị ở phần tử giữa\n* First quartile (Q1): Trung vị giữa Median và phần tử nhỏ nhất trong tập dữ liệu. Còn gọi là 25th Percentile.\n* Third quartile (Q3): Trung vị giữa Median và phần tử lớn nhất trong tập dữ liệu. Còn gọi là 75th Percentile.\n* Minimum: Phần tử nhỏ nhất không phải ngoại lệ.\n* Maximum: Phần tử lớn nhất không phải là ngoại lệ.\n* Outliers: Các ngoại lệ, là các điểm dữ liệu khác biệt đáng kể so với các điểm dữ liệu còn lại\n\n","metadata":{}},{"cell_type":"code","source":"def boxPlot(x,y,data,title):\n    sb.boxplot(x=x,y=y,data=data)\n    plt.grid(True)\n    plt.title(title)\n\n# boxplot: Độ dài của câu\nplt.subplot(2,3,1)\nboxPlot('target', 'question_length', train_df, 'question_length of each question class')\n\n# boxplot: Số lượng từ\nplt.subplot(2,3,2)\nboxPlot('target', 'number_of_words', train_df, 'number_of_words of each question class')\n\n# boxplot: Số lượng từ không bị trùng\nplt.subplot(2,3,3)\nboxPlot('target', 'number_of_unique_words', train_df, 'number_of_unique_words of each question class')\n\n# boxplot: Số lượng stopwords\nplt.subplot(2,3,4)\nboxPlot('target', 'number_of_stopwords', train_df, 'number_of_stopwords of each question class')\n\n# boxplot: Số lượng ký tự đặc biệt\nplt.subplot(2,3,5)\nboxPlot('target', 'number_special', train_df, 'number_special of each question class')\n\nplt.subplots_adjust(right=3.0)\nplt.subplots_adjust(top=2.0)\nplt.show()\n\n\n\n","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:19.623766Z","iopub.execute_input":"2022-01-08T10:08:19.624390Z","iopub.status.idle":"2022-01-08T10:08:21.480875Z","shell.execute_reply.started":"2022-01-08T10:08:19.624351Z","shell.execute_reply":"2022-01-08T10:08:21.480187Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"**Nhận xét**:\n* Các insincere question có độ dài câu hỏi, số lượng từ, số lượng ký tự đặc biệt nhìn chung lớn hơn so với các sincere question (ngoại trừ một vài outliers của sincere).\n    * insincere có thể là các câu hỏi spam, quảng cáo,...\n    * Dựa vào số lượng ký hiệu đặc biệt, insincere có thể là các công thức toán học latex, các câu hỏi chứa các icon,... \n* Ta nhìn thấy outliers ở boxplot question_length của sincere xấp sỉ 800. Ta sẽ xem đây là câu hỏi như nào. Đồng thời ta sẽ xem câu hỏi có độ dài lớn nhất là 1000 của insincere là câu hỏi như nào.\n","metadata":{}},{"cell_type":"markdown","source":"#### Phân tích đặc trưng độ dài","metadata":{}},{"cell_type":"code","source":"train_df_insincere = pd.DataFrame(train_df[train_df['target']==1], columns =['question_text','target','question_length'])\ntrain_df_insincere.head()","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:21.481920Z","iopub.execute_input":"2022-01-08T10:08:21.482282Z","iopub.status.idle":"2022-01-08T10:08:21.554739Z","shell.execute_reply.started":"2022-01-08T10:08:21.482245Z","shell.execute_reply":"2022-01-08T10:08:21.553926Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Sort tập training ở lớp insincere từ lớn đến nhỏ \ntrain_df_insincere.sort_values('question_length', inplace = True, ascending = False)\ntrain_df_insincere.head(10)","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:21.556345Z","iopub.execute_input":"2022-01-08T10:08:21.556624Z","iopub.status.idle":"2022-01-08T10:08:21.576076Z","shell.execute_reply.started":"2022-01-08T10:08:21.556589Z","shell.execute_reply":"2022-01-08T10:08:21.575369Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def topQuestionIn(data,noOfQues):\n    listTop = data.tolist()\n    for i in range(0,noOfQues):\n        print('Question',i)\n        print(listTop[i]+'\\n')","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:21.577175Z","iopub.execute_input":"2022-01-08T10:08:21.577486Z","iopub.status.idle":"2022-01-08T10:08:21.582271Z","shell.execute_reply.started":"2022-01-08T10:08:21.577450Z","shell.execute_reply":"2022-01-08T10:08:21.581549Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Ta in ra 10 câu hỏi dài nhất ở lớp insincere","metadata":{}},{"cell_type":"code","source":"topQuestionIn(train_df_insincere['question_text'],10)  ","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:21.583454Z","iopub.execute_input":"2022-01-08T10:08:21.584178Z","iopub.status.idle":"2022-01-08T10:08:21.599042Z","shell.execute_reply.started":"2022-01-08T10:08:21.584140Z","shell.execute_reply":"2022-01-08T10:08:21.598065Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Làm tương tự với lớp sincere\ntrain_df_sincere = pd.DataFrame(train_df[train_df['target']==0], columns =['question_text','target','question_length'])\ntrain_df_sincere.sort_values('question_length', inplace = True, ascending = False)\n\ntopQuestionIn(train_df_sincere['question_text'],10)  \n\n","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:21.600449Z","iopub.execute_input":"2022-01-08T10:08:21.600963Z","iopub.status.idle":"2022-01-08T10:08:22.007997Z","shell.execute_reply.started":"2022-01-08T10:08:21.600928Z","shell.execute_reply":"2022-01-08T10:08:22.007187Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"**Nhận xét:** \n* Ta thấy câu có độ dài lớn nhất của insincere là được viết bằng công thức toán học Latex\n* Câu hỏi có độ dài 800 từ của sincere là một câu hỏi liên quan đến phim ảnh, còn câu hỏi có độ dài thứ nhì là một câu hỏi toán học Latex \n* Ta chuyển đổi 3 câu hỏi toán học ở trong top các từ dài nhất ở 2 lớp sang dạng latex view: \n    * 2 hình ảnh ở lớp insincere:\n    \n    ![Screen Shot 2022-01-03 at 18.06.34.png](attachment:e8894300-0bca-4f46-ba33-11049bd35dc8.png)\n    ![Screen Shot 2022-01-03 at 18.07.52.png](attachment:19d43e51-be48-4424-a0c5-ac7d235a6ccd.png)\n    \n    * hình ảnh ở lớp sincere:\n    \n    ![Screen Shot 2022-01-03 at 18.14.41.png](attachment:8cb76091-f684-4226-8438-0df9a900bf0d.png)\n    \n* Ta thấy các câu hỏi toán học được đánh dấu ở hai lớp ở trên không có vấn đề gì đáng ngờ. Tuy nhiên có khả năng vì nhiều ký tự đặc biệt nên chúng bị đánh dấu insincere\n    \n    \n    \n","metadata":{},"attachments":{"e8894300-0bca-4f46-ba33-11049bd35dc8.png":{"image/png":"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"},"19d43e51-b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"},"8cb76091-f684-4226-8438-0df9a900bf0d.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"# 3. Tiền xử lý và clean dữ liệu ","metadata":{}},{"cell_type":"markdown","source":"Quá trình tiền xử lý dữ liệu gồm:\n* Loại bỏ các ký tự đặc biệt có trong câu hỏi\n* Xử lý các misspell words (các từ viết/phát âm không chính xác)\n* Xử lý các Contractions (những từ có dấu nháy đơn ['])\n* Loại bỏ số \n* Loại bỏ các tag toán học, đường dẫn","metadata":{}},{"cell_type":"code","source":"# Loại bỏ các ký tự đặc biệt\ndef remove_special_character(text):\n    text = str(text)\n    for c in special_character_list: # special_character_list khi chạy boxplot ký tự đặc biệt\n        if c in text:\n            text = text.replace(c,'')\n    return text","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:22.009715Z","iopub.execute_input":"2022-01-08T10:08:22.009982Z","iopub.status.idle":"2022-01-08T10:08:22.015348Z","shell.execute_reply.started":"2022-01-08T10:08:22.009947Z","shell.execute_reply":"2022-01-08T10:08:22.014600Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#Xử lý các misspell \nmispell_dict = {'colour': 'color', 'centre': 'center', 'favourite': 'favorite', 'travelling': 'traveling', 'counselling': 'counseling', 'theatre': 'theater', 'cancelled': 'canceled', 'labour': 'labor', 'organisation': 'organization', 'wwii': 'world war 2', 'citicise': 'criticize', 'youtu ': 'youtube ', 'Qoura': 'Quora', 'sallary': 'salary', 'Whta': 'What', 'narcisist': 'narcissist', 'howdo': 'how do', 'whatare': 'what are', 'howcan': 'how can', 'howmuch': 'how much', 'howmany': 'how many', 'whydo': 'why do', 'doI': 'do I', 'theBest': 'the best', 'howdoes': 'how does', 'mastrubation': 'masturbation', 'mastrubate': 'masturbate', \"mastrubating\": 'masturbating', 'pennis': 'penis', 'Etherium': 'bitcoin', 'narcissit': 'narcissist', 'bigdata': 'big data', '2k17': '2017', '2k18': '2018', 'qouta': 'quota', 'exboyfriend': 'ex boyfriend', 'airhostess': 'air hostess', \"whst\": 'what', 'watsapp': 'whatsapp', 'demonitisation': 'demonetization', 'demonitization': 'demonetization', 'demonetisation': 'demonetization', \n                'electroneum':'bitcoin','nanodegree':'degree','hotstar':'star','dream11':'dream','ftre':'fire','tensorflow':'framework','unocoin':'bitcoin',\n                'lnmiit':'limit','unacademy':'academy','altcoin':'bitcoin','altcoins':'bitcoin','litecoin':'bitcoin','coinbase':'bitcoin','cryptocurency':'cryptocurrency',\n                'simpliv':'simple','quoras':'quora','schizoids':'psychopath','remainers':'remainder','twinflame':'soulmate','quorans':'quora','brexit':'demonetized',\n                'iiest':'institute','dceu':'comics','pessat':'exam','uceed':'college','bhakts':'devotee','boruto':'anime',\n                'cryptocoin':'bitcoin','blockchains':'blockchain','fiancee':'fiance','redmi':'smartphone','oneplus':'smartphone','qoura':'quora','deepmind':'framework','ryzen':'cpu','whattsapp':'whatsapp',\n                'undertale':'adventure','zenfone':'smartphone','cryptocurencies':'cryptocurrencies','koinex':'bitcoin','zebpay':'bitcoin','binance':'bitcoin','whtsapp':'whatsapp',\n                'reactjs':'framework','bittrex':'bitcoin','bitconnect':'bitcoin','bitfinex':'bitcoin','yourquote':'your quote','whyis':'why is','jiophone':'smartphone',\n                'dogecoin':'bitcoin','onecoin':'bitcoin','poloniex':'bitcoin','7700k':'cpu','angular2':'framework','segwit2x':'bitcoin','hashflare':'bitcoin','940mx':'gpu',\n                'openai':'framework','hashflare':'bitcoin','1050ti':'gpu','nearbuy':'near buy','freebitco':'bitcoin','antminer':'bitcoin','filecoin':'bitcoin','whatapp':'whatsapp',\n                'empowr':'empower','1080ti':'gpu','crytocurrency':'cryptocurrency','8700k':'cpu','whatsaap':'whatsapp','g4560':'cpu','payymoney':'pay money',\n                'fuckboys':'fuck boys','intenship':'internship','zcash':'bitcoin','demonatisation':'demonetization','narcicist':'narcissist','mastuburation':'masturbation',\n                'trignometric':'trigonometric','cryptocurreny':'cryptocurrency','howdid':'how did','crytocurrencies':'cryptocurrencies','phycopath':'psychopath',\n                'bytecoin':'bitcoin','possesiveness':'possessiveness','scollege':'college','humanties':'humanities','altacoin':'bitcoin','demonitised':'demonetized',\n                'brasília':'brazilia','accolite':'accolyte','econimics':'economics','varrier':'warrier','quroa':'quora','statergy':'strategy','langague':'language',\n                'splatoon':'game','7600k':'cpu','gate2018':'gate 2018','in2018':'in 2018','narcassist':'narcissist','jiocoin':'bitcoin','hnlu':'hulu','7300hq':'cpu',\n                'weatern':'western','interledger':'blockchain','deplation':'deflation', 'cryptocurrencies':'cryptocurrency', 'bitcoin':'blockchain cryptocurrency',}\n\ndef correct_mispell(x):\n    words = x.split()\n    for i in range(0, len(words)):\n        if mispell_dict.get(words[i]) is not None:\n            words[i] = mispell_dict.get(words[i])\n        elif mispell_dict.get(words[i].lower()) is not None:\n            words[i] = mispell_dict.get(words[i].lower())\n        \n    words = \" \".join(words)\n    return words","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:22.016963Z","iopub.execute_input":"2022-01-08T10:08:22.017215Z","iopub.status.idle":"2022-01-08T10:08:22.038715Z","shell.execute_reply.started":"2022-01-08T10:08:22.017177Z","shell.execute_reply":"2022-01-08T10:08:22.037802Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#Loại bỏ các stopwords\ndef remove_stopwords(text):\n    text = [word for word in text.split() if word not in STOPWORDS]\n    text = ' '.join(text)\n    return text","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:22.040077Z","iopub.execute_input":"2022-01-08T10:08:22.040933Z","iopub.status.idle":"2022-01-08T10:08:22.050131Z","shell.execute_reply.started":"2022-01-08T10:08:22.040893Z","shell.execute_reply":"2022-01-08T10:08:22.049333Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#Xử lý các contraction\ncontraction_map = {\"ain't\": \"is not\", \"aren't\": \"are not\",\"can't\": \"cannot\", \"'cause\": \"because\", \"could've\": \"could have\", \"couldn't\": \"could not\", \"didn't\": \"did not\",  \"doesn't\": \"does not\", \"don't\": \"do not\", \"hadn't\": \"had not\", \"hasn't\": \"has not\", \"haven't\": \"have not\", \"he'd\": \"he would\",\"he'll\": \"he will\", \"he's\": \"he is\", \"how'd\": \"how did\", \"how'd'y\": \"how do you\", \"how'll\": \"how will\", \"how's\": \"how is\",  \"I'd\": \"I would\", \"I'd've\": \"I would have\", \"I'll\": \"I will\", \"I'll've\": \"I will have\",\"I'm\": \"I am\", \"I've\": \"I have\", \"i'd\": \"i would\", \"i'd've\": \"i would have\", \"i'll\": \"i will\",  \"i'll've\": \"i will have\",\"i'm\": \"i am\", \"i've\": \"i have\", \"isn't\": \"is not\", \"it'd\": \"it would\", \"it'd've\": \"it would have\", \"it'll\": \"it will\", \"it'll've\": \"it will have\",\"it's\": \"it is\", \"let's\": \"let us\", \"ma'am\": \"madam\", \"mayn't\": \"may not\", \"might've\": \"might have\",\"mightn't\": \"might not\",\"mightn't've\": \"might not have\", \"must've\": \"must have\", \"mustn't\": \"must not\", \"mustn't've\": \"must not have\", \"needn't\": \"need not\", \"needn't've\": \"need not have\",\"o'clock\": \"of the clock\", \"oughtn't\": \"ought not\", \"oughtn't've\": \"ought not have\", \"shan't\": \"shall not\", \"sha'n't\": \"shall not\", \"shan't've\": \"shall not have\", \"she'd\": \"she would\", \"she'd've\": \"she would have\", \"she'll\": \"she will\", \"she'll've\": \"she will have\", \"she's\": \"she is\", \"should've\": \"should have\", \"shouldn't\": \"should not\", \"shouldn't've\": \"should not have\", \"so've\": \"so have\",\"so's\": \"so as\", \"this's\": \"this is\",\"that'd\": \"that would\", \"that'd've\": \"that would have\", \"that's\": \"that is\", \"there'd\": \"there would\", \"there'd've\": \"there would have\", \"there's\": \"there is\", \"here's\": \"here is\",\"they'd\": \"they would\", \"they'd've\": \"they would have\", \"they'll\": \"they will\", \"they'll've\": \"they will have\", \"they're\": \"they are\", \"they've\": \"they have\", \"to've\": \"to have\", \"wasn't\": \"was not\", \"we'd\": \"we would\", \"we'd've\": \"we would have\", \"we'll\": \"we will\", \"we'll've\": \"we will have\", \"we're\": \"we are\", \"we've\": \"we have\", \"weren't\": \"were not\", \"what'll\": \"what will\", \"what'll've\": \"what will have\", \"what're\": \"what are\",  \"what's\": \"what is\", \"what've\": \"what have\", \"when's\": \"when is\", \"when've\": \"when have\", \"where'd\": \"where did\", \"where's\": \"where is\", \"where've\": \"where have\", \"who'll\": \"who will\", \"who'll've\": \"who will have\", \"who's\": \"who is\", \"who've\": \"who have\", \"why's\": \"why is\", \"why've\": \"why have\", \"will've\": \"will have\", \"won't\": \"will not\", \"won't've\": \"will not have\", \"would've\": \"would have\", \"wouldn't\": \"would not\", \"wouldn't've\": \"would not have\", \"y'all\": \"you all\", \"y'all'd\": \"you all would\",\"y'all'd've\": \"you all would have\",\"y'all're\": \"you all are\",\"y'all've\": \"you all have\",\"you'd\": \"you would\", \"you'd've\": \"you would have\", \"you'll\": \"you will\", \"you'll've\": \"you will have\", \"you're\": \"you are\", \"you've\": \"you have\" }\ndef clean_contractions(text):\n    specials = [\"’\", \"‘\", \"´\", \"`\"]\n    for s in specials:\n        text = text.replace(s, \"'\")\n    \n    text = ' '.join([contraction_map[t] if t in contraction_map else t for t in text.split(\" \")])\n    return text\n    ","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:22.053625Z","iopub.execute_input":"2022-01-08T10:08:22.053835Z","iopub.status.idle":"2022-01-08T10:08:22.070309Z","shell.execute_reply.started":"2022-01-08T10:08:22.053804Z","shell.execute_reply":"2022-01-08T10:08:22.069541Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# loại bỏ số\ndef clean_numbers(text):\n    text = re.sub('[0-9]{5,}', '#####', text)\n    text = re.sub('[0-9]{4}', '####', text)\n    text = re.sub('[0-9]{3}', '###', text)\n    text = re.sub('[0-9]{2}', '##', text)\n    return text","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:22.071900Z","iopub.execute_input":"2022-01-08T10:08:22.072387Z","iopub.status.idle":"2022-01-08T10:08:22.083002Z","shell.execute_reply.started":"2022-01-08T10:08:22.072345Z","shell.execute_reply":"2022-01-08T10:08:22.082303Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#Lemamatizing\n\"\"\"\nword_lemmatizer = WordNetLemmatizer()\ndef lemma_word(text):\n    text = text.split()\n    text =[word_lemmatizer.lemmatize(w) for w in text]\n    return ' '.join(text)\n\"\"\"","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:22.084443Z","iopub.execute_input":"2022-01-08T10:08:22.084948Z","iopub.status.idle":"2022-01-08T10:08:22.094368Z","shell.execute_reply.started":"2022-01-08T10:08:22.084906Z","shell.execute_reply":"2022-01-08T10:08:22.093561Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Xóa bỏ các tag toán học, đường dẫn \ndef clean_tag(x):\n    if '[math]' in x:\n        x = re.sub('\\[math\\].*?math\\]', 'MATH EQUATION', x) #replacing with [MATH EQUATION]\n    \n    if 'http' in x or 'www' in x:\n        x = re.sub('(?:(?:https?|ftp):\\/\\/)?[\\w/\\-?=%.]+\\.[\\w/\\-?=%.]+', 'URL', x) #replacing with [url]\n    return x","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:22.099730Z","iopub.execute_input":"2022-01-08T10:08:22.100300Z","iopub.status.idle":"2022-01-08T10:08:22.106558Z","shell.execute_reply.started":"2022-01-08T10:08:22.100258Z","shell.execute_reply":"2022-01-08T10:08:22.105089Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def clean_data(text):\n    text = clean_tag(text)\n    text = clean_contractions(text)\n    text = correct_mispell(text)\n    text = clean_numbers(text)\n    text = remove_special_character(text)\n    return text","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:22.109219Z","iopub.execute_input":"2022-01-08T10:08:22.109655Z","iopub.status.idle":"2022-01-08T10:08:22.115372Z","shell.execute_reply.started":"2022-01-08T10:08:22.109615Z","shell.execute_reply":"2022-01-08T10:08:22.114410Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_df['preprocessed_question_text'] = train_df['question_text'].apply(lambda x: clean_data(x))\ntest_df['preprocessed_question_text'] = test_df['question_text'].apply(lambda x: clean_data(x))","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:08:22.118536Z","iopub.execute_input":"2022-01-08T10:08:22.119026Z","iopub.status.idle":"2022-01-08T10:09:41.717183Z","shell.execute_reply.started":"2022-01-08T10:08:22.118994Z","shell.execute_reply":"2022-01-08T10:09:41.716461Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_df.head(20)","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:09:41.718321Z","iopub.execute_input":"2022-01-08T10:09:41.718592Z","iopub.status.idle":"2022-01-08T10:09:41.733239Z","shell.execute_reply.started":"2022-01-08T10:09:41.718558Z","shell.execute_reply":"2022-01-08T10:09:41.732564Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_df.head(20)","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:09:41.734532Z","iopub.execute_input":"2022-01-08T10:09:41.734970Z","iopub.status.idle":"2022-01-08T10:09:41.750074Z","shell.execute_reply.started":"2022-01-08T10:09:41.734934Z","shell.execute_reply":"2022-01-08T10:09:41.749402Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"embed_size = 300\nmax_features = 150000\nmaxlen = 70\nn_epochs = 10\nn_splits = 5\n\nbatch_size = 512\n\ndevice = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\nprint(device)","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:09:41.751260Z","iopub.execute_input":"2022-01-08T10:09:41.752895Z","iopub.status.idle":"2022-01-08T10:09:41.801463Z","shell.execute_reply.started":"2022-01-08T10:09:41.752858Z","shell.execute_reply":"2022-01-08T10:09:41.800712Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Sau khi tiền xử lý, làm sạch dữ liệu. Ta sẽ tiến hành các bước như sau\n\n![](https://miro.medium.com/max/1218/1*zsIXWoN0_CE9PXzmY3tIjQ.png)\n\n\n","metadata":{}},{"cell_type":"code","source":"train_X = train_df['preprocessed_question_text'].values\ntest_X = test_df['preprocessed_question_text'].values\ntokenizer = Tokenizer(num_words = max_features)\n\n#tokenizer từ trong tập train và tập huấn luyện\ntokenizer.fit_on_texts(list(train_X)+list(test_X))\n\ntrain_X = tokenizer.texts_to_sequences(train_X)\ntest_X = tokenizer.texts_to_sequences(test_X)\n\n# tạo một dict để mapping từ và số thứ tự\nword_index = tokenizer.word_index # type: dict\n\n# reize lại mảng để có độ dài bằng nhau\ntrain_X = pad_sequences(train_X,maxlen = maxlen)\ntest_X = pad_sequences(test_X, maxlen=maxlen)\n\ntrain_Y = train_df['target'].values","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:09:41.803691Z","iopub.execute_input":"2022-01-08T10:09:41.803955Z","iopub.status.idle":"2022-01-08T10:10:50.911078Z","shell.execute_reply.started":"2022-01-08T10:09:41.803922Z","shell.execute_reply":"2022-01-08T10:10:50.910338Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Ta sẽ sử dụng bộ pre trained embedding của glove đã được cho sẵn bởi cuộc thi ","metadata":{}},{"cell_type":"code","source":"!unzip ../input/quora-insincere-questions-classification/embeddings.zip","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:10:50.912307Z","iopub.execute_input":"2022-01-08T10:10:50.912571Z","iopub.status.idle":"2022-01-08T10:14:26.980233Z","shell.execute_reply.started":"2022-01-08T10:10:50.912538Z","shell.execute_reply":"2022-01-08T10:14:26.979402Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def load_glove(word_index):\n    EMBEDDING_FILE = './glove.840B.300d/glove.840B.300d.txt'\n    def get_coefs(word,*arr): return word, np.asarray(arr, dtype='float32')[:300]\n    \n    f = open(EMBEDDING_FILE,encoding=\"utf-8\")\n    embeddings_index = dict(get_coefs(*o.split(\" \")) for o in f)\n    \n    all_embs = np.stack(embeddings_index.values())\n    emb_mean,emb_std = -0.005838499,0.48782197\n    embed_size = all_embs.shape[1]\n\n    # word_index = tokenizer.word_index\n    nb_words = min(max_features, len(word_index))\n    embedding_matrix = np.random.normal(emb_mean, emb_std, (nb_words, embed_size))\n    for word, i in word_index.items():\n        if i >= max_features: continue\n        embedding_vector = embeddings_index.get(word)\n        #ALLmight\n        if embedding_vector is not None: \n            embedding_matrix[i] = embedding_vector\n        else:\n            embedding_vector = embeddings_index.get(word.capitalize())\n            if embedding_vector is not None: \n                embedding_matrix[i] = embedding_vector\n    return embedding_matrix ","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:14:26.983652Z","iopub.execute_input":"2022-01-08T10:14:26.983884Z","iopub.status.idle":"2022-01-08T10:14:26.993018Z","shell.execute_reply.started":"2022-01-08T10:14:26.983856Z","shell.execute_reply":"2022-01-08T10:14:26.992357Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"glove_embedding = load_glove(tokenizer.word_index)\n#fasttext_embedding = load_wiki(tokenizer.word_index)\n#para_embedding = load_para(tokenizer.word_index)\n#embedding_matrix = np.mean([glove_embedding, fasttext_embedding, para_embedding], axis = 0)\nembedding_matrix = glove_embedding","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:14:26.994543Z","iopub.execute_input":"2022-01-08T10:14:26.995087Z","iopub.status.idle":"2022-01-08T10:19:03.447180Z","shell.execute_reply.started":"2022-01-08T10:14:26.995052Z","shell.execute_reply":"2022-01-08T10:19:03.446440Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(embedding_matrix.shape)","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:19:03.448589Z","iopub.execute_input":"2022-01-08T10:19:03.448863Z","iopub.status.idle":"2022-01-08T10:19:03.455176Z","shell.execute_reply.started":"2022-01-08T10:19:03.448811Z","shell.execute_reply":"2022-01-08T10:19:03.454419Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Ta sử dụng phương pháp K-fold, để chia tập training. Phần dữ liệu training thì sẽ được chia thành K phần (K ở đây ta cho bằng 5). Sau đó train model K lần, mỗi lần train sẽ chọn 1 phần làm dữ liệu validation và K-1 phần con lại làm training set. Kết quả cuối cùng sẽ là trung bình cộng kết quả đánh giá của K lần train\n\n\n![](https://web888.vn/wp-content/uploads/2021/09/image-108.png)\n","metadata":{}},{"cell_type":"code","source":"splits = list(StratifiedKFold(n_splits=5, shuffle=True, random_state=2000).split(train_X, train_Y))","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:19:03.456554Z","iopub.execute_input":"2022-01-08T10:19:03.457016Z","iopub.status.idle":"2022-01-08T10:19:03.657930Z","shell.execute_reply.started":"2022-01-08T10:19:03.456980Z","shell.execute_reply":"2022-01-08T10:19:03.657126Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"","metadata":{}},{"cell_type":"code","source":"device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu') \nprint(device)","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:19:03.659053Z","iopub.execute_input":"2022-01-08T10:19:03.659303Z","iopub.status.idle":"2022-01-08T10:19:03.670170Z","shell.execute_reply.started":"2022-01-08T10:19:03.659270Z","shell.execute_reply":"2022-01-08T10:19:03.669418Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 4. Mô hình sử dụng\n## 4.1 Mô hình hồi quy Logistic\n* Đã được giảng viên dạy: https://excessive-source-1c9.notion.site/16-09-2021-H-i-quy-Logistics-cdcc911147e5458ba9203b58e6bd0099\n* Notebook cho xử lý bài toán bằng mô hình hồi quy logistic: https://www.kaggle.com/dinhvietahn19021217/toxic-quora-question/notebook\n* Điểm số đạt được: private score: 0.36198, public score: 0.36785\n\n\n## 4.2 Mô hình Bidirectional LSTM\n#### RNN (Recuurent Neural Networks)\n* RNN là một mạng neural networks cho phép các đầu ra trước đó được sử dụng làm đầu vào khi có các trạng thái ẩn. \n* Trong lý thuyết ngôn ngữ, ngữ nghĩa của câu được tạo thành từ một chuỗi các từ trong câu theo một cấu trúc ngữ pháp. Do đó cần phải có một kiến trúc mạng đặc biệt cho neural netwwork biểu diễn chuỗi từ này nhằm mục đích liên kết các từ liền trước với các từ hiện tại để tạo ra mối liên hệ xâu chuỗi. RNN đã được thiết kế để giải quyết yêu cầu này\n\n##### Mô hình\n![Screen Shot 2022-01-08 at 12.09.51.png](attachment:6ebdd3b4-d466-4293-a079-8d60b910f7cd.png)\n\n* Mô hình gồm t input, các input được đưa vào mô hình đúng với thứ tự từ trong câu\n* Mỗi hình vuông được gọi là 1 state, đầu vào mỗi state là $ x_t $, $h_{t-1}$ với $h_t = f(W*x_t + U*h_{t-1})$. (W là trọng số của đầu vào, U là trọng số của trạng thái ẩn), $f$ là activation value như: sigmoid, tanh, ReLU,....\n* Có thể thấy $h_t$ mang cả thông tin từ hidden state trước \n* $h_0$ được thêm vào để cho chuẩn công thức nên thường được gán bằng 0 hoặc giá trị ngẫu nhiên\n* $y_t = g(V*h_t)$. V là trọng số của trạng thái ẩn sau khi tính đầu ra\n\n#### LSTM (Long short term memory)\n* Điểm yếu của RNN là không học được các thông tin trước đó ở xa do bị vanishing graident. Mạng LSTM ra đời để khắc phục điểm yếu này \n\n![Screen Shot 2022-01-08 at 12.15.57.png](attachment:f71fd52b-c21e-4b88-b2fc-f61b418dc7de.png)\n\n* Ở state thứ t của mô hình\n    * output: $c_t$  là cell state, $h_t$ là hidden state     \n    * input: $c_{t-1},h_{t-1}$. Ở đây $c$ là điểm mới so với RNN\n* Tính toán trong ô LSTM:\n    * Cổng quên (forget gate): $\\mathbf f_t = \\sigma(\\mathbf W_{f} \\mathbf x_t + \\mathbf U_{f}\\mathbf h_{t-1})$\n    * Cổng đầu vào (input gate): $\\mathbf i_t = \\sigma(\\mathbf W_{i} \\mathbf x_t + \\mathbf U_{i}\\mathbf h_{t-1})$\n    * Cổng đầu ra (output gate): $\\mathbf o_t = \\sigma(\\mathbf W_{o} \\mathbf x_t + \\mathbf U_{o}\\mathbf h_{t-1})$\n    * $\\tilde{\\mathbf c}_t = \\mathrm{tanh}(\\mathbf W_{c} \\mathbf x_t + \\mathbf U_{c}\\mathbf h_{t-1})$\n    * Cổng trạng thái ô (cell state): $\\mathbf c_{t} = \\mathbf f_t \\times \\mathbf c_{t-1} + \\mathbf i_t \\times \\tilde{\\mathbf c}_t$. Forget gate quyết định xem lấy bao nhiêu từ cell state trước và input gate sẽ quyết định lấy bao nhiêu từ input của state và hidden state của state trước\n    * $ \\mathbf h_t = \\mathrm{tanh}(c_t) \\times \\mathbf o_t $ , $\\mathbf y_t = \\phi_y(\\mathbf W_y \\mathbf h_t)$\n* Ta thấy LSTM là RNN được hiệu chỉnh bởi $c_t$, thông tin nào cần quan trọng và dùng ở sau sẽ được gửi vào và dùng khi cần => có thể mang thông tin đi xa\n\n#### Bidirectional LSTM \n\n![](https://production-media.paperswithcode.com/methods/Screen_Shot_2020-05-25_at_8.54.27_PM.png)\n\n* Bidirectional LSTM là mô hình gồm hai LSTM: LSTM thứ nhất nhận đầu vào là chuỗi các từ theo thứ tự từ trái sang phải, LSTM còn lại nhận đầu vào là chuỗi các từ theo thứ tự từ phải sang trái. Điều này làm tăng hiệu quả lượng thông tin có sẵn, đồng thời cải thiện ngữ cảnh có sẵn cho thuật toán.\n\n\n#### Kiến trúc mô hình sử dụng\n* Lớp Embedding layer sử dụng embbeding của glove\n* BiLSTM\n* 2 lớp linear, với hàm kích hoạt relu\n* dropout 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6U6fPu1xIaqfVoFMaV0ByyOAAAIIIIAAAsEQ0OFyLVq0SHRVRYoUkZYtWyb6Hi8iYFeAHl+7UuRDAAEEEEAAAQQQcLQAga+jm4/CI4AAAggggAACCNgVIPC1K0U+BBBAAAEEEEAAAUcLEPg6uvkoPAIIIIAAAggggIBdAQJfu1LkQwABBBBAAAEEEHC0AIGvo5uPwiOAAAIIIIAAAgjYFSDwtStFPgQQQAABBBBAAAFHCxD4Orr5KDwCCCCAAAIIIICAXQECX7tS5EMAAQQQQAABBBBwtACBr6Obj8IjgAACCCCAAAII2BUg8LUrRT4EEEAAAQQQQAABRwsQ+Dq6+Sg8AggggAACCCCAgF0BAl+7UuRDAAEEEEAAAQQQcLQAga+jm4/CI4AAAggggAACCNgVIPC1K0U+BBBAAAEEEEAAAUcLEPg6uvkoPAIIIIAAAggggIBdAQJfu1LkQwABBBBAAAEEEHC0AIGvo5uPwiOAAAIIIIAAAgjYFSDwtStFPgQQQAABBBBAAAFHCxD4Orr5KDwCCCCAAAIIIICAXQECX7tS5EMAAQQQQAABBBBwtACBr6Obj8IjgAACCCCAAAII2BUg8LUrRT4EEEAAAQQQQAABRwsQ+Dq6+Sg8AggggAACCCCAgF0BAl+7UuRDAAEEEEAAAQQQcLQAga+jm4/CI4AAAggggAACCNgVIPC1K0U+BBBAAAEEEEAAAUcLEPg6uvkoPAIIIIAAAggggIBdAQJfu1LkQwABBBBAAAEEEHC0AIGvo5uPwiOAAAIIIIAAAgjYFSDwtStFPgQQQAABBBBAAAFHCxD4Orr5KDwCCCCAAAIIIICAXQECX7tS5EMAAQQQQAABBBBwtACBr6Obj8IjgAACCCCAAAII2BUg8LUrRT4EEEAAAQQQQAABRwsQ+Dq6+Sg8AggggAACCCCAgF0BAl+7UuRDAAEEEEAAAQQQcLQAga+jm4/CI4AAAggggAACCNgVIPC1K0U+BBBAAAEEEEAAAUcLEPg6uvkoPAIIIIAAAggggIBdAQJfu1LkQwABBBBAAAEEEHC0AIGvo5uPwiOAAAIIIIAAAgjYFSDwtStFPgQQQAABBBBAAAFHCxD4Orr5KDwCCCCAAAIIIICAXQECX7tS5EMAAQQQQAABBBBwtACBr6Obj8IjgAACCCCAAAII2BUg8LUrRT4EEEAAAQQQQAABRwsQ+Dq6+Sg8AggggAACCCCAgF0BAl+7UuRDAAEEEEAAAQQQcLRAJkeXnsIHJHDx4kXZuWu3bNu2TbZt3y5xsbEBrSelhTJmzCRDh72eUraA38+RM6eULVNGypS5UUqXKiWZMrE7B4xpc0Hdd3bt1n1nu2z17T+h2neiMmSQ198YbrNUqc+m+06ZG2+UsmXLSKnrr5fMmTOnfiUsgQACCCDgOIGoq77kuFJT4IAErly5IrO/nCPjJ06SggXySYXyZaR8uRslV64cAa0vvRc6ezZWNm/ZLps2b5Njx09Kp6f/Jn994H7J4Aua0iNdvnxZYn0HEfqRio6OTo8ihGybuu/MmfuV/Gv8BCmQP69UrFDW0fvOuXNx8fvO0WMn5OkOT8lDD/413fadkDUcKw66gH6+4+Li5Pz581KgQIGgr58VJhRo3ry59OrVS2rVqpXwDf5CIEABAt8A4Zy2mAZkvV94UbJlyyTdn+sghQsVdFoVki3vocNH5Z9vTZSLF6/IsKFDJGeO8AbzTZs2ldmzZ4sGiG3btpXJkycnW14nvRnr+5F/oe+Lvl7RjGbfiSnsrn3n8JH/7DsXLlyUN4YNlZy+3mASAokJjB07Vrp16yaXLl2SmJgYOXjwYGLZPPOangE6ePCQ7N23T86ePRuSer/66mBp1qy5VKxYMSTr1zOFRXxtWbxEcYnOnTsk22ClkSVA4BtZ7RGS0mgw9mzXblLjtqryWMuHQ7KNSFnph1M/kzW/bZJRb44Ia+/d3r17pW/fvjJ16lRXBb6673Tt3lOqVa0obVo/EinNHJJyTPv4c1nxy28yZvSosO47IakMKw2JwKlTp+Sjjz6SZ5991tOB77Hjx2WC78zhggXfS5EihaVUqRKSJ/q6kJifjzsvWbJmkYwZM4Zk/RcvXvIF7gd9w//2SP58+aRTx6elzh21Q7ItVhoZAgyKjIx2CGkpPpo6TfLmuc71Qa8ianC2Zetwmf7xJ9L6sUdD6uq/8hIlSvjGi5b1f8kVz9UxV85srg96tbEea9XEN255p0ydNl3aPN7aFe1HJYIrkCdPHqlWrVpwV+qwtf2w6EcZPmKktGz+oHw56/2QBaTpwbJl6w5z5nDuV/Okf7+XJHv27OlRDLYZYoH0GQwZ4kqx+v8J6OmnadM/lh5d//a/F13+7PnuHWXKR1PNeNtwVlXH+Gpyy7B5HR6jjj27PR1OxnTdln5ONPA9d+5cupaDjUeugJ4F0WQ9Rm5Jg1+yBd99L2PHjZN/jRkqrVo85KqgV7XKlb1Bxo4eIiVLFJJuPXqaIS3BV2SN6S1A4JveLRDi7X/97QKpf9cdct11uUK8pchZfbTvlFu9O2vJN766hzNZAa/+IC5cuFAeffRRqVKlitx5550ya9ascBYlKNtSv7vq3u67UC80pzCDUsggr0Q/J/p5+fqb8O47Qa4GqwuhgPU518cdO3ZIly5dpEaNGlK9enUZOHCgWAfAISxCuqxaxzO/OWqUjBjWXwoWzJ8uZQjXRv+v3aNSoniMGc4Rrm2ynfAJEPiGzzpdtvTrr79KrRreOzVX01fn1atXp4v5okWLZMSIEfLMM8/IgAEDZPHixdK6dWs5evRoupQn0I3qvqOOXkv6eVn16yqvVZv6plJAzwro51oPbCdNmiTHjh0zn/fPPvsslWtyRvY3R42Wp596XAoV8sZMFl27PCXz5s+XAwe8fQGjM/bO1JWSMb6p83Jc7uPHT7j+6DyxRink65E4fuJEYm+F/DWd6kgvcsvtu0JYr/7W6dUuXLggGzZskHr16sVvf+nSpWY4RsOGDeNfi6QnJ06elEIF3N2zk5i39mYd9128Q0IgOQGdzmzw4MHSqFEjk+2mm24SvchVD7hbtGhhhjw1a9bMDAfQac903vS8efP6vo8Lym7fXNh16tQxF8Qmtw3/9/TCuilTpshzzz3n/3JYnh/xzXyyefMWGdS/R1i2FwkbyZYtq7TwjWP+ZMYM6d6tayQUiTIESYAe3yBBRupqrl694skr1DXYTK8xePoDqEGvJp0qJ0uWLOb5H3/8YR71B1B7g//2t7+lW6+0KUgK/1O/qAxRKeRy39tRUXwtuq9VQ1OjmjVrxq84a9as5rn1OV+2bJnv5jplZNq0aTJ69GhZvny5+cy//fbbpmdYD4btJj2DpDNJDBo0yO4iQc23zFf2O+vUkKgob30f1K9bW5YsXRZUS1aW/gJ8w6d/G1AClwhYPwpWoGtVyxoTaAXi+mM4zneBSNWqVa0sPCKAgEMErM+5Fvfaz7q+Zn3Ov/32WxPg6sHvqlWrRAPi2rX/M02WTs2Vmnlpn3/+eXnhhRd09emSDh46JMWLFUmXbafnRvXsz0nfmS+SuwQY6uCu9qQ2ESCQXneOi4CqUwQEPCXgHwRfW/HOnTtLjv/eSOeHH34Q7R22bo6iUx9WqFDh2kUi9u/LviFbmTOF96ZAEYPhsV7uiHEPYUHo8Q0hLqv2joBe8axj8DTp2L+dO3fK77//Ltu3b4+f3sw/j3dkqCkC7hE4ffq07N+/P75C+jnXIQu7du0ytzHWN86cOWPy+N/OWAPf+vXrxy+XK1eugOaItc4exa8ojE+uytUwbo1NIRA6AXp8Q2fLmj0k0LVrV9HZHIoWLSpbt26VBg0ayJdffil169Y1F7RoL7Deb/6E74K7nj17GhntLUrPHzIPNQ9VRSAoAjpet1+/fr67lRUxn9077vBNfff119KuXTszq4N+/vXW5Yd8QwPmzJljtqlDHH7++edEhyrs2bNH3n333STLpt8V1vUCyfUuJ7kC3kAAgT8JEPj+iYQXEEi9wAzflb+JJQ10k0sEvsnp8B4CkSXQqVMn0X/XpvXr11/7UvzfK1euNLO7+F8IZ71ZsmRJMw7Y+julR74vUhLifQRSFmCoQ8pG5EAgqAL646XDIXTaM50LVB9JCCDgLgG9kYUOf/riiy+kfPnyZkiEdeFbamt68eJFM4RCp0fUdbr1JhmpdSE/AoEIEPgGosYyCKRBQE+DDhgwQHTaM/0h1Ls9kRBAwF0COn3ZkCFDzDy+9913nwwbNkyS6xlOrvYffPCBGTqlc/gOHTpUfvrpp+Sy8x4CCCQjwFCHZHB4C4FQCOj4QP0RJCGAgHsFdOoya/qytNbyqaeeSusqWB4BBP4rQI8vuwICCCCAAAIIIICAJwQIfD3RzFQSAQQQQAABBBBAIOChDjovYWxsrLlIp3nz5kgigAACCCCAAAIIIBDRAgEHvg899JCcPXtWMmfOLAS+Ed3GFA4BBBBAAAEEEEDAJxBw4KuT9VevXh1EBBBAAAEEEEAAAQRSLfD555/Lxo0bzdSeOtPR448/nup1pHaBgMf4WvcgT+0GyR9cASY0D66nl9bGvuOl1g5uXfVWvcePHw/uSlkbAgh4TmDDhg0yZswYM/Xf/Pnzw1L/gANfawJt/wm59R7lR44cCUrB9d7nEydONHMW6gTgpMQFVq1aJf/3f/9nbpGZeA5eRSBxgTVr1siTTz4pBw8eTDwDryKQhEC+fPmkQIEC0qFDBzl58mQSuXgZAQQQSF7gpZdeMt8jyecK7rsBB75Wb5E+6r3K9Z7ltWrVkpiYGPN4+PDhgEuqwZzOW7hlyxbJmTOnfPLJJ+b+6AGv0MUL3nrrrfLee++Ze8d37tw5aAceLiajav8VqFatmrz//vtStGhR6dixo6TlMwuqtwSio6Pl2WeflUmTJskNN9wgffv2NXcU85YCtUUAAZ3k4I8//kgTRIYMAYeiAW034DG+1ta0x1fvTvPll1+K9gI0bNhQvvvuOxk/fry88sorVrZUPY4bN04ee+yx+KOAJk2ayAsvvCALFiww60/VyjyQeeHChfLwww+bH6GpU6fKE088IX//+99Nj4wHqk8V0yDw448/ygMPPGAC4I8//ljatGlj9p2CBQumYa3OX/TkiRPm7lhRUVGi//SL2f/R/7n1XiS8Fk75wYMHy4cffmgC3lGjRsk777wjevCt39W5c+cOZ1HYVhoFtNd+ypQp5jeXYYxpxPTY4lmyZDHXezVt2tTEfDrhQWrTtSMItm/fLjoEQr9H9CYwgawzuTKkOfDVlWvgq0GvpmLFipnHPXv2mEf9344dO2TWrFlmTFiZMmXMqfn4NxN5oqdgdZ1WKlGihFx//fWmV6pw4cLJ/ggF68fHaeu57rrrzL3c9chLDzr0S0wDmmw5clqMnntc7Lut52233Zbs/hJJQUt6lSVPnjyyd+9ec9Q+YcIEE8zoLVZz5Y723D5jVVi/v/QAXA/s9ayW/rOeW4+R9ppVTqsOaX30/w70f+6/n+o29b0LFy6Yf6+//rr57v7mm2+kUaNGtoqg44WzZ89uzhb6L7B27VopXbq05MqVy/9l+eWXX+Tmm2+WTJmC8vOVYN1e/SNv3rzmwKVbt24yfPhw6dKli2TLls2rHNQ7FQIalGrnpB4I6+/Hq6++Ku3atQvo83nq1CnTiaczhmlP8ooVK6RBgwamMzUVRUoxa1C+OYoXLx6/If1S1HTx4kXzeOnSJbn//vtFZ4HQoLVx48ZStmxZufPOO837if1P8+k9zQsVKhT/9oEDB8xwh7vvvjvFH6Fg/SA5aT3xUL4naq874+LFi6Ve/Qb+b3nq+W01ashrgweluL9EaiBjlct6DNb+eO36/HcK3Xf0CP4n30HD3Y3u8X/LU8+r+gKrd8aN9VSdr62s7m/++5z/c92HNNitUKGCyaPL6gGUDnsYMWKE3HXXXdeuLsm/dZy5Lvfuu+/G59H116tXz5x90GDMStoTpAezOo+8vk8KnoB2TlWuXNmYDx06VF5++WV55plnJGvWrMHbiEPXpD2S1gGfQ6sQ0mLr2X3tcDt06JD06NHD9Py+9tpr0rZtW8mYMaPtbc+bN09mzJghzZo1M9cO5M+fX77//nvR4a+33HKLiW00GE4qaWzpHzcmlS8ogW9i3dD6JalJC6kV12BWU82aNU3vb3KBb+vWrc3R5/nz501P78yZM02PgAbQ1nrMyvifEVi6dKmMHDnS9LzoqQE1fuONN6RKlSrydKdnPKukX9hFihTxbP3tVHzlypXx+46O29Qx49rjU7VqVXmmy7N2VkEelwpoT67V05tYFfXiY+2h0YC3XLlyJuCtU6dOYlmTfe2jjz76U++iBhnLly8XPdvnn2688UZZt26dVKxY0f/lFJ9/9dVXor3QVn38H/2fW8GNV1/T08o6/El72zSY0TOv/fr1k6gM9oOXFBvDYRn27N5lDsysA0ErtglGNXQ/c8u+VqpUKXNvB+2t1X96wKoX3us1Wi1atLDFpTGLBr2a9CyE/obrAbZ1Ae2cOXNMbKMBtX73vPjii2ZGCD0rNHbsWNEL5XTYZ0opKIGvNpyVrOfWo35J6QVqVtLneqoquaTzuGkwrafrdZYIvXBOT70Q9Caupl9WmnRog55q1LnwSAjYEajh6xXXdO+995ovlEqVKtlZjDweF9Afo+7du5uzdx988IG5oDlQEmt43LXLa+9NYukvf/lLYi8n+5r+KGtQbgUv1lkP61Fft55bj6l5TXsE/fP7Pw9kfdYy1mO41qczvGiwoZ1O586dk99//90EMH97uqMUiUn6LG2y+A5/s+T1peTb+V+FpBbartY/q62tx3C1ubU96zHQ7erwMOtMv8ZvehCpNzrTjji7STtf/JMVR+rIAU16UKbXeuk4dL2+QM8UaWyoSWcV0wNwOyngwFdPi1hp+vTp5u5tGtBu3brVvLxt2zb57LPPTLSuAP4pLi7O/89En7ds2VL0Hyl5Ae3trV+/vhmPWL58+eQz8y4CfgJ6NuYu3ylpPVJObQ+a32p46kGBTZs2iZ4t0DMETkjaGUCHQPItpcFFyZIlTdCr43v1n/bYaS/ax5/MSH5h3g1IQAM7K7hLzZCAgDYWwoX0GhGNRbQuGrzq3XwHDhwYf81XSpu2DJIat6/BuCadOcy6+FKDYP39spIOcUjqYNnKYz0GHPiuXr1aHn30UXO0ouMBdeiCjrvS6cx0RgaN/PVv/WK0jgJ0o3rxlZ4aIwVHQH11DAwJgdQK6HRmOiMICYHUCujFZSR3CejYbO3x1d9nnd5QZ+fQ080kBFIS0J5dHR6j+43OKBXsIYZWYNyqVav4omh8qcNwrOT/nvVaUo8BB76ffvrpn9aZ2NG/3orOGp+hC2h3tF6cQAqOQGLjq4OzZtbidgH2Hbe3MPVDwJ6Adk5ZFyONHj3a9NrZW5JcXhc4evSomcBg7ty5Zk741Hq89dZbostq2rx5sxla06dPH9NjbHWa6j6pQzH0Oi9Nu3fvNqMLAr3ANeDA12zdxv/0FKqOG9QLC3Q84ZIlS0SHRpAQQAABBBBAIP0FdDzv/v37RafFJCGQGgGd810PmgJNeu2Wjh7Q+w/ocBvt3dVOGb2QVa9Z0r91pID/+F+dJUyHNeg0t4GkkAe+Wqhp06aZqWp0TOHkyZP/dKVuIAVnGQQQQAABBBBIuwBDGtJuyBoCE0jqWi4dapNU0mEOyc0MltRy1uthCXx1JofnnnvO2iaPCCCAAAIIIIAAAgjYFtC7i2oH6uzZs0Vvhta/f38z33Rq55oOS+Bru1ZkRAABBBBAAAEEEEDgGgG9o2jDhg3NHNPWtGupDXp1lQS+18DyJwIIIIAAAggggEBkCegNuoKREk6wG4w1sg4EEEAAAQQQQAABBCJQgMA3AhuFIiGAAAIIIIAAAggEX4DAN/imrBEBBBBAAAEEEEAgAgUIfCOwUSgSAggggAACCCCAQPAFCHyDb8oaEUAAAQQQQAABBCJQgMA3AhuFIiGAAAIIIIAAAggEX4DAN/imrBEBBBBAAAEEEEAgAgUIfCOwUSgSAgikr8CVK1fTtwBsHQEEEEAgJAIEviFhjZyV6u2iz5w5FzkFClNJtM5ad1LgAup39qz39h2tc65c7DuB7zksiQACCESuAIFv5LZNUEpWsWJFWbt+U1DW5aSVrF23SW7y1Z0UuID6/bbWi/vORvadwHcblnShwFXfCZAo338kBNwgQODrhlZMpg73Nb5HZs/5Rrx06vbKlSsy56sF0viee5KR4a2UBNRPHdXTK0k/J7Pnfiv3+j43JAQQ+I9A1qxZ5PyFC57juKoRP8l1AgS+rmvShBUqUaKEVK5USWZ8+mXCN1z81/RPZku1ajdLsWJFXVzL0FdN/dTx45ne2Xf0c6KfF/3ckBBA4D8CpUuXlm3bd3uOY+euPVK8eDHP1dvtFSbwdXsL++r3fM8e8tnn82T9hi2ur60OcfhiztfSo1s319c1HBVUx89nzxd1dXvSz4d+TvTzQkIAgf8J1KpVU5av+NVzvb7zv/lB7q5f/38QPHOFQMYBvuSKmlCJJAWyZc0q1W6+Wfq+NECyZ88m5cvdmGReJ7+hAdqoMZNkxBuvS9GiRZxclYgpe1bfvlO9enV5wbfvZPOd7qxQvkzElC2YBZn95dfy5ugJMvz1YZwpCCYs63KFQJbMmeXEyZPy79/Wyq3Vq7iiTilV4tDhozJm7HvySr+XJEuWLCll530HCUT5xrAwiMVBDZaWoh45clTeGD5CDh0+KHVq3+YLYspK+fI3+mY/yJGW1abbsrHnYmXTlu2yadM2+ennFb5TUsWll6+3rmDBgulWJrdu+OjRozJ85Juyb98+ufOOGlKhQhmp4DuAyunQ2Q9iY+Nk82bfvrN5qyxeslJiCheR3r2el0KF2Hfcug9Tr7QJnD9/Xtq0bS99nn9Gbq76l7StLMKXvnTpknTp9rK0fqy13NOoYYSXluKlVoDAN7ViLsi/ZctWWfPvf/uGPqz3BY1bJDY2NiS1si6KypAhNCNqcuXK5QvAyslfbvqL3HxzVSlbxp29kSFpnABXunXbNlm9eo1s2LjB7DvnzoVmurNw7DvlfQd+Zt+pWlXKlSsboAiLIeAdgW3bt8tzXbtLz+5PS906tVxZ8VOnz8grA173dQpVlOd7dHdlHb1eKQJfr+8BIaz/Qw89JHqqfMaMGSHcCqt2o0Dz5s1Fe10+//xzN1aPOiHgWIG9e/dK/4GDJF+e3NKy+YNSpXJFCVXnRjiRjh49Ll9/u0g++2KePPVkO2napIlERTGFWzjbIFzbIvANl7THtnP48GHRK4H1i2P37t1SoEABjwlQ3UAFdFhFqVKlREdh7dy5UwoXLhzoqlgOAQRCIKBnZL5f+IMs+vFHWb9+g1y+fEly5AjdkDn9LghVEHr58hXRM1c6k8utt1SXpk2bSIH8+UOgxiojRYDAN1JawmXl6Ny5s0ycONF8WXXs2FFGjx7tshpSnVAJdO3aVd555x0T+Hbo0EHGjh0bqk2xXgQQCIJAXFyc6L9QpF9++UWGDRsWsjOHGTNmlOjoaFf0WofC343rJPB1Y6umc520t7d8+fJy+vRpUxL9Utm6dSsXnaVzuzhh89rbW7Zs2QT7zubNm+n1dULjUUYEQiBwxx13yJIlS2Tjxo2+azoqhGALrNJrAqG56shritQ3gcDAgQMTHP3r1cCDBw9OkIc/EEhMYNCgQaL7i5W0F0n3JxICCHhPYOXKlbJhwwbTG9u7d2/vAVDjkAjQ4xsSVu+uVHt7Y2Ji5LrrrhM9haRJL1LSMVRHjhyh19e7u0aKNdfe3kKFConO1pEpUyYz1EHHEp49e1YOHTpEr2+KgmRAwF0CderUMb29OsZXzxwuW7aMXl93NXG61CZTumyVjbpWoFevXqZu48aNk/3795sARufVbdu2rfTt21cmTZrk2rpTsbQJvPDCC2YFOqZXg2A9YCpWrJi0adNGdL+aMmVK2jbA0ggg4BgB7e1dv369OQDWQusBsPb6fvmld26h7pjGclhBGergsAaL5OJqoGJNQ/X444+b01M6zc0TTzxhghid3uzy5cuRXAXKlk4Cul88/PDDZj/R/UX3G/2n+5G1X7HvpFPjsFkE0kGgR48ecurUKXP2UO+cplNjLliwwDd/uPtvn54O3J7aJIGvp5o7tJXV09MavFhDHPy3pq8l9Z5/Pp57UyC5/SO597ypRa0RcLeADmn4+eefpW7dujJq1Ch54IEHpE+fPnLhwgVp3LixuytP7UIuQOAbcmI2gAACCCCAAAJ2BdasWSM61GHRokVmhiDtVBkwYICZ7UWnytRrSUgIBCrAGN9A5VgOAQQQQAABBIIu0KlTp0TXmTt3brGuBUg0Ay8iYEOAHl8bSGRBAAEEEEAAAQQQcL4Aga/z25AaIIAAAggggAACCNgQIPC1gUQWBBBAAAEEEEAAAecLEPg6vw2pAQIIIIAAAggggIANAQJfG0hkQQABBBBAAAEEEHC+AIGv89uQGiCAAAIIIIAAAgjYECDwtYFEFgQQQAABBBBAAAHnCxD4Or8NqQECCCCAAAIIIICADQECXxtIZEEAAQQQQAABBBBwvgCBr/PbkBoggAACCCCAAAII2BAg8LWBRBYEEEAAAQQQQAAB5wsQ+Dq/DakBAggggAACCCCAgA0BAl8bSGRBAAEEEEAAAQQQcL4Aga/z25AaIIAAAggggAACCNgQIPC1gUQWBBBAAAEEEEAAAecLEPg6vw2pAQIIIIAAAggggIANAQJfG0hkQQABBBBAAAEEEHC+AIGv89uQGiCAAAIIIIAAAgjYECDwtYFEFgQQQAABBBBAAAHnCxD4Or8NqQECCCCAAAIIIICADQECXxtIZEEAAQQQQAABBBBwvgCBr/PbkBoggAACCCCAAAII2BAg8LWBRBYEEEAAAQQQQAAB5wsQ+Dq/DakBAggggAACCCCAgA0BAl8bSGRBAAEEEEAAAQQQcL4Aga/z25AaIIAAAggggAACCNgQIPC1gUQWBBBAAAEEEEAAAecLEPg6vw2pAQIIIIAAAggggIANAQJfG0hkQQABBBBAAAEEEHC+AIGv89uQGiCAAAIIIIAAAgjYECDwtYFEFgQQQAABBBBAAAHnCxD4Or8NqQECCCCAAAIIIICADQECXxtIZEEAAQQQQAABBBBwvgCBr/PbkBoggAACCCCAAAII2BAg8LWBRBYEEEAAAQQQQAAB5wsQ+Dq/DakBAggggAACCCCAgA0BAl8bSGRBAAEEEEAAAQQQcL4Aga/z25AaIIAAAggggAACCNgQIPC1gUQWBBBAAAEEEEAAAecLEPg6vw2pAQIIIIAAAggggIANAQJfG0hkQQABBBBAAAEEEHC+AIGv89uQGiCAAAIIIIAAAgjYECDwtYFEFgQQQAABBBBAAAHnC2RyfhWoQSQKTJkyRWbNmiUZMmSQPHnySPv27SOxmJQpAgWmTZsmX3zxhSlZoUKFpG3bthFYSoqEAAIIIOBEAQJfJ7ZahJd5yJAhsmbNGhk8eLBcuXJF3n//fTl06JD07ds3wktO8dJbYNiwYbJ06VLp2bOnXLp0SaZPny779u2Tl156Kb2LxvYRQAABBFwgEHXVl1xQD6oQIQKxsbFy6623yrJlyyQ6OtqUav/+/dK8eXNZsGCB5MyZM0JKSjEiTeD8+fNyyy23yOrVqyVr1qymeLt27ZJHHnlEvvvuO8mbN2+kFZnyIIBACAV2794tEyZMkLlz58prr70m999/fwi3xqq9IsAYX6+0dJjquWfPHilatGh80KubLVasmOTKlcv03IWpGGzGgQLas6tDG6ygV6tQqlQpKVCgAPuOA9uTIiOQFgE989OxY0e5cOGCPP744zJ58mR59dVX07JKlkXACDDUgR0hqALaK5cvXz5Zvny51KxZ06x74cKFJoDR4JeEQFICejZAx4Pr2YJatWqZbD/88IMULFhQsmXLltRivI4AAi4UeOutt6RNmzbmn1ZPzxx26NDBnBGqVq2aC2tMlcIlQOAbLmmPbCcmJkbuuusuGTlypNxzzz2iI2lWrFghVatWNT2/HmGgmgEI6JmCe++9V0aMGCH16tUz48M3bNggt99+u5QtWzaANbIIAgg4VWDTpk0yfvz4+OLrmcPKlSvLunXrhMA3noUnAQgQ+AaAxiLJC3Tp0kVKly4tS5YsMRkffPBB0X8kBFIS6NSpkwlytadXU9OmTaVx48bmOf9DAAHvCJQpU8acObz77rtNpU+dOiVxcXGSO3du7yBQ05AIcHFbSFhZKQIIIIAAAggEKjBp0iT5+uuvRQ+GtbdXpzk8duyYDB8+nKFPgaKynBEg8GVHQAABBBBAAIGIE9D54D/99FM5ceKEGUKnY37LlSsXceWkQM4SIPB1VntRWgQQQAABBBBAAIEABZjOLEA4FkMAAQQQQAABBBBwlgCBr7Pai9IigAACCCCAAAIIBChA4BsgHIshgAACCCCAAAIIOEuAwNdZ7UVpEUAAAQQQQAABBAIUIPANEI7FEEAAAQQQQAABBJwlQODrrPaitAgggAACCCCAAAIBChD4BgjHYggggAACCCCAAALOEiDwdVZ7UVoEEEAAAQQQQACBAAUyBbgciyEg7733nkRFRUmGDBnkjz/+kDvvvFOyZ88u33zzjWTJkkUuXbokt956q1SpUgUtBBIITJ48Wa5evRq/79xxxx2SK1cuc4tSa9+pXr263HzzzQmW4w8EEEAAAQTSIkDgmxY9jy/7/fffy8aNG2XVqlUmgNH7qufLl0/69u0rOXLkkNtuu00KFixI4Ovx/SSx6lv7zsqVK82+M3fuXImJiZEXX3xRsmXLJjVq1DD7EoFvYnq8hgACCCAQqACBb6ByLCd6H/W4uDjT0/vrr7+KBi8a7GqaP3++3HTTTX9S2rlzp5QuXfpPr/OCtwS0x/f8+fNSr1490eBX9506derIlStXZN68eVKpUqUEIFu2bJHff//d7FMZM2ZM8B5/IIAAAgggYFcgyne68ardzORDIDGB3bt3mx66I0eOSM6cOWX27NnSoEGDBFn/+c9/yrJly+Tf//636SVO8CZ/eFZg7969Zt85dOiQOUvw+eefS6NGjRJ49OnTR66//nr58ccfZf369bJgwQLTO5wgE38ggIDjBN58801ZuHChZMqUSS5evCjVqlWTQYMGySOPPGIOgrVCN9xwg4wcOdJxdaPAkSvAxW2R2zaOKZkGJSNGjDDl1eOo6OjoP5X9ySeflM6dO5txv396kxc8K1CiRIn4H7XE9p2tW7fK9OnTpUmTJvLxxx+bMeSjR4/2rBcVR8BNArVq1ZKmTZvKTz/9JHPmzJGzZ8+a6l24cMEModP3Gjdu7KYqU5cIEGCoQwQ0gtOLcPLkSfnHP/4htWvXliVLlpij9eXLlyfolUssGHZ6vSl/2gVOnz4tQ4YMid93mjVrJrrvFC1a1Ky8SJEi8uijj5ozCfqCDpM5duxY2jfMGhBAIN0Fbr/9dtF/egB83333yfjx46VAgQLmd0SvA9ALXK00c+ZMef/9983vig6T0t8d/T6IjY0VPWM0bdo0yZs3r5WdRwSSFKDHN0ka3rAjoKenWrZsaS5gW7x4sbRv31727NkjLVq0MGMy7ayDPN4U0H2nVatWUqFCBdPj06FDB9m3b580b95ctMdHk8708Prrr0uePHnk1KlT8sMPP0i7du28CUatEXCpQMOGDc3nXK8Z6devn+hZHf+gV6utw6D0zOLEiROlbNmyZmjE22+/bYJhnVmIzhWX7hwhqBaBbwhQvbJKPVLXq+51zKUepevUZlWrVjXV1yBYpzF76qmnEnAwpDwBh2f/sPYdnQlEZ/7QHy5r2rulS5ea/UoPovxT165d5Y033hCd+oyEAALuEtDOEj3Q1fTBBx+YwNaq4cGDB83UmOXLlzcvLVq0SOrXr2+9bX539DuEhIAdAS5us6NEnkQFdEyWTj2l8/XqNGY6BdWGDRtk165dZh7fy5cvmwuWdH5fTTqOS8f6btu2LdH18aJ3BPz3He3N1bF+OjWezvqh8/jqvqNzQtetW9eg6HCIypUry4MPPmiGQtSsWdM7WNQUAZcL6HAFneFFe3l1hiCdIvO5554zPb9a9XPnzpmOFb14WnuFtaPlu+++M8Mk9P0DBw7ED4/Sv0kIJCdA4JucDu8FVUADX+3F2759e1DXy8rcLaCnM3UssPYS6w+gnk0YNmyYuytN7RDwgICO19dhTXo2R8fpak+udpzojY/OnDkjY8aMMQe7xYoVE2saQx37qxe7Hj9+XDJnzuwBJaoYbAEC32CLsr5EBXTaGms6M53qrE2bNuaCpkQz8yIC/xXQswN6SlN7gK2kF1IyztfS4BEB5wroxazac6vD5HSebr1gTc8a6nCmrFmzmorp6/paqVKlzN/9+/c3c3/rfN8kBAIRIPANRI1lEEAAAQQQQCDsAjr8SWeA0Ls8khAIRIDR4IGosQwCCCCAAAIIhFVAb3izYsWKRO8KGtaCsDFHC9Dj6+jmo/AIIIAAAgi4X6B3795mpgedvUFvba5DH7p37+7+ilPDoAsQ+AadlBUigAACCCCAAAIIRKIAQx0isVUoEwIIIIAAAggggEDQBQh8g07KChFAAAEEEEAAAQQiUYDANxJbhTIhgAACCCCAAAIIBF2AwDfopKwQAQQQQAABBBBAIBIFCHwjsVUoEwIIIIAAAggggEDQBQh8g07KChFAAAEEEEAAAQQiUYDANxJbhTIhgAACCCCAAAIIBF2AwDfopKwQAQQQQAABBBBAIBIFCHwjsVUoEwIIIIAAAggggEDQBQh8g07KChFAAAEEEEAAAQQiUYDANxJbhTIhgAACCCCAAAIIBF3g/wHfdU93Vm32GgAAAABJRU5ErkJggg=="},"f71fd52b-c21e-4b88-b2fc-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"}}},{"cell_type":"code","source":"class LSTM_Model(nn.Module):\n    def __init__(self):\n        super().__init__()\n        \n        self.embedding = nn.Embedding(150000, 300)\n        self.embedding.weight.data.copy_(torch.from_numpy(embedding_matrix))\n        self.embedding.weight.requires_grad = False\n        self.lstm = nn.LSTM(300, 64, bidirectional=True, batch_first=True)\n        self.fc1 = nn.Linear(64*2 , 64)\n        self.fc2 = nn.Linear(64,1)\n        self.relu = nn.ReLU()\n        self.dropout = nn.Dropout(0.1)\n    \n    def forward(self, x):\n        out = self.embedding(x)\n        out, (h,c) = self.lstm(out)\n        cat = torch.cat((h[-2,:,:],h[-1,:,:]),dim=1) # đầu ra của hai hướng LSTM sẽ được kết hợp ở trạng thái cuối \n        out = self.relu(cat)\n        out = self.dropout(self.fc1(out))\n        out = self.fc2(out)\n        return out\n","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:19:03.671511Z","iopub.execute_input":"2022-01-08T10:19:03.671983Z","iopub.status.idle":"2022-01-08T10:19:03.682218Z","shell.execute_reply.started":"2022-01-08T10:19:03.671946Z","shell.execute_reply":"2022-01-08T10:19:03.681355Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"","metadata":{}},{"cell_type":"code","source":"# Ở phần thực hiện training em tham khảo đoạn code: https://www.kaggle.com/oysiyl/107-place-solution-using-public-kernel","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:19:30.703306Z","iopub.execute_input":"2022-01-08T10:19:30.703864Z","iopub.status.idle":"2022-01-08T10:19:30.707893Z","shell.execute_reply.started":"2022-01-08T10:19:30.703824Z","shell.execute_reply":"2022-01-08T10:19:30.706871Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Thuật toán huấn luyện:\n* Lấy một fold trong tập fold đã được chia:\n    * Lặp epoch = 1,2,...\n        * mô hình thực hiện forward\n        * Tính đạo hàm và cập nhật trọng số của mô hình\n        ","metadata":{}},{"cell_type":"code","source":"train_epochs = 6\nx_test = torch.tensor(test_X, dtype=torch.long).to(device)\ntest = torch.utils.data.TensorDataset(x_test)\ntest_loader = torch.utils.data.DataLoader(test, batch_size=batch_size, shuffle=False)\n\n\n\ntrain_preds= np.zeros((len(train_X)))\ntest_preds = np.zeros((len(test_X)))\nfor i_fold, (train_idx, valid_idx) in enumerate(splits):\n\n    x_train_fold = torch.tensor(train_X[train_idx], dtype=torch.long).to(device)\n    y_train_fold = torch.tensor(train_Y[train_idx, np.newaxis], dtype=torch.float32).to(device)\n    x_val_fold = torch.tensor(train_X[valid_idx], dtype=torch.long).to(device)\n    y_val_fold = torch.tensor(train_Y[valid_idx, np.newaxis], dtype=torch.float32).to(device)\n    \n    train = torch.utils.data.TensorDataset(x_train_fold, y_train_fold)\n    valid = torch.utils.data.TensorDataset(x_val_fold, y_val_fold)\n    \n    #Load data \n    train_loader = torch.utils.data.DataLoader(train, batch_size=batch_size, shuffle=True)\n    valid_loader = torch.utils.data.DataLoader(valid, batch_size=batch_size, shuffle=False)\n    \n    # mô hình \n    model = LSTM_Model().to(device)\n    # hàm loss và adam optimizer\n    criterion = torch.nn.BCEWithLogitsLoss(reduction='sum')\n    optimizer = torch.optim.Adam(model.parameters(), lr=0.001)\n\n    print(f'Fold {i_fold + 1}')\n    \n    avg_losses_f = []\n    avg_val_losses_f = []\n\n    for epoch in range(train_epochs):\n        model.train()\n        avg_loss = 0.\n        for batch_i,(x_batch, y_batch) in enumerate(train_loader):\n            # lan truyền tới \n            y_pred = model(x_batch)\n            # tính hàm mất mát\n            loss = criterion(y_pred, y_batch)\n\n            optimizer.zero_grad()\n            # lan truyền ngược \n            loss.backward()\n            # cập nhật lại trọng số mô hình\n            optimizer.step()\n            \n            avg_loss += loss.item() / len(train_loader)\n            \n        # Kiểm tra mô hình với tập validation \n        model.eval()\n        valid_preds_fold = np.zeros(x_val_fold.size(0))\n        test_preds_fold = np.zeros(len(test_X))\n        \n        avg_val_loss = 0.\n        for batch_i, (x_batch, y_batch) in enumerate(valid_loader):\n            y_pred = model(x_batch).detach()\n            avg_val_loss += criterion(y_pred, y_batch).item() / len(valid_loader)\n            valid_preds_fold[batch_i * batch_size:(batch_i+1) * batch_size] = torch.sigmoid(y_pred.cpu())[:, 0]\n\n        print('Epoch {}/{} \\t loss={:.2f} \\t val_loss={:.2f}'.format(epoch + 1, train_epochs, avg_loss, avg_val_loss))\n        avg_losses_f.append(avg_loss)\n        avg_val_losses_f.append(avg_val_loss)\n    # Biểu đồ sau mỗi fold\n    plt.figure(figsize=(10,5))\n    plt.title(f'Loss During Training in Fold {i_fold + 1}')\n    plt.plot(avg_losses_f,label=\"training\")\n    plt.plot(avg_val_losses_f,label=\"valid\")\n    plt.xlabel(\"Epoch\")\n    plt.ylabel(\"Loss\")\n    plt.legend()\n    plt.show()\n\n    # Dự đoán tập test sau mỗi fold \n    for batch_i, (x_batch,) in enumerate(test_loader):\n        y_pred = model(x_batch).detach()\n        test_preds_fold[batch_i * batch_size:(batch_i+1) * batch_size] = torch.sigmoid(y_pred.cpu())[:, 0]\n\n    train_preds[valid_idx] = valid_preds_fold\n    test_preds += test_preds_fold / len(splits)\n","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:19:33.723386Z","iopub.execute_input":"2022-01-08T10:19:33.723716Z","iopub.status.idle":"2022-01-08T10:39:05.282488Z","shell.execute_reply.started":"2022-01-08T10:19:33.723683Z","shell.execute_reply":"2022-01-08T10:39:05.281751Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from sklearn.metrics import f1_score\ndef bestThresshold(y_train,train_preds_):\n    thres = 0.0\n    max_f1 = 0.0 \n    for t in np.arange(0.1, 0.5, 0.01):\n        t = np.round(t,2)\n        f1_score_ = f1_score(y_train,np.array(train_preds_)>t)\n        if f1_score_ > max_f1:\n            thres = t\n            max_f1 = f1_score_\n    print(thres,max_f1)\n    return thres \n\nbestThres = bestThresshold(train_Y,train_preds)","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:40:41.196764Z","iopub.execute_input":"2022-01-08T10:40:41.197338Z","iopub.status.idle":"2022-01-08T10:40:56.563947Z","shell.execute_reply.started":"2022-01-08T10:40:41.197298Z","shell.execute_reply":"2022-01-08T10:40:56.563173Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"submission = test_df[['qid']].copy()\nsubmission['prediction'] = (test_preds > bestThres).astype(int)\nsubmission.to_csv('submission.csv', index=False)","metadata":{"execution":{"iopub.status.busy":"2022-01-08T10:41:10.289522Z","iopub.execute_input":"2022-01-08T10:41:10.290119Z","iopub.status.idle":"2022-01-08T10:41:11.086203Z","shell.execute_reply.started":"2022-01-08T10:41:10.290082Z","shell.execute_reply":"2022-01-08T10:41:11.085431Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 5. Kết luận\n* Mô hình BiLSTM cho ra số điểm tốt hơn nhiều so với mô hình hồi quy logistc\n* Có thể kết hợp nhiều pre trained embedding để cải thiện chất lượng trong quá trình preprocessing","metadata":{}},{"cell_type":"markdown","source":"\n","metadata":{}},{"cell_type":"markdown","source":"","metadata":{}}]}