{"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":"**BÁO CÁO BÀI TẬP LỚN HỌC MÁY CUỐI KỲ**\n\n**Mã Lớp**: INT3405_1\n\n**Họ và tên**: Phạm Ngọc Dũng\n\n**Mã số sinh viên**: 18020378","metadata":{}},{"cell_type":"markdown","source":"# Giới thiệu bài toán\nQuora là một nền tảng cho phép mọi người học hỏi lẫn nhau. Trên Quora, mọi người có thể đặt câu hỏi và kết nối với những người khác, những người đóng góp thông tin chi tiết độc đáo và câu trả lời chất lượng.Vì là một nền tảng mở ai cũng có thể đọc và hỏi đáp một cách dễ dàng nên sẽ có những người đưa ra những định kiến, những câu hỏi mang tính độc hại chia rẽ.\n\nBài toán đặt ra là ta cần phân loại được đâu là những câu hỏi chân thành (Sincere) và không chân thành (Insincere).\n\ninput: câu hỏi dạng text\n\noutput: 1/0(không chân thành/ chân thành)","metadata":{}},{"cell_type":"markdown","source":"Import thư viện cần thiết","metadata":{}},{"cell_type":"code","source":"#import thư viện\nimport os\nimport time\nimport numpy as np\nimport pandas as pd \nfrom tqdm import tqdm\nimport math\nfrom sklearn.model_selection import train_test_split\nfrom sklearn import metrics\n\nfrom keras.preprocessing.text import Tokenizer\nfrom keras.preprocessing.sequence import pad_sequences\nfrom keras.layers import GlobalMaxPool1D, Dropout, Activation,CuDNNLSTM\nfrom keras.layers import MaxPooling1D, BatchNormalization,Conv2D,Flatten\nfrom keras.layers import Bidirectional, GlobalMaxPool1D,CuDNNLSTM\nfrom keras.layers import Dense, Input , LSTM , Embedding , Conv1D , Bidirectional , GRU , Dropout, CuDNNGRU\nfrom keras.models import Model\nfrom keras import initializers, regularizers, constraints, optimizers, layers\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom nltk.stem import PorterStemmer\nfrom nltk.tokenize import word_tokenize\nfrom nltk.corpus import stopwords","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2022-01-07T17:11:48.512958Z","iopub.execute_input":"2022-01-07T17:11:48.513701Z","iopub.status.idle":"2022-01-07T17:11:54.308583Z","shell.execute_reply.started":"2022-01-07T17:11:48.51361Z","shell.execute_reply":"2022-01-07T17:11:54.307855Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Đọc dữ liệu","metadata":{}},{"cell_type":"code","source":"train_df = pd.read_csv(\"../input/quora-insincere-questions-classification/train.csv\")\ntest_df = pd.read_csv(\"../input/quora-insincere-questions-classification/test.csv\")\ntrain_df.info()\nprint(\"Train shape : \",train_df.shape)\nprint(\"Test shape : \",test_df.shape)","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:11:54.310422Z","iopub.execute_input":"2022-01-07T17:11:54.310689Z","iopub.status.idle":"2022-01-07T17:11:59.402603Z","shell.execute_reply.started":"2022-01-07T17:11:54.310655Z","shell.execute_reply":"2022-01-07T17:11:59.401841Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Xem qua 1 vài ví dụ về dữ liệu tập train","metadata":{}},{"cell_type":"code","source":"train_df.head()","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:11:59.403788Z","iopub.execute_input":"2022-01-07T17:11:59.404553Z","iopub.status.idle":"2022-01-07T17:11:59.420638Z","shell.execute_reply.started":"2022-01-07T17:11:59.404513Z","shell.execute_reply":"2022-01-07T17:11:59.419859Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"xem qua 1 vài ví dụ tập test","metadata":{}},{"cell_type":"code","source":"test_df.head()","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:11:59.423408Z","iopub.execute_input":"2022-01-07T17:11:59.423625Z","iopub.status.idle":"2022-01-07T17:11:59.433619Z","shell.execute_reply.started":"2022-01-07T17:11:59.4236Z","shell.execute_reply":"2022-01-07T17:11:59.432592Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"dữ liệu gồm 3 cột thông tin:\n\nqid: ID câu hỏi\n\nquestion_text: nội dung câu hỏi-> cần được phân loại\n\ntarget: kết quả của các câu hỏi:0/1(chân thành/ không chân thành)\n\ndữ liệu tập train có 1306122 questions, tập test là 375806 questions","metadata":{}},{"cell_type":"markdown","source":"# Phân tích dữ liệu","metadata":{}},{"cell_type":"code","source":"target = train_df['target']\ntarget_1 = 0\nfor target_value in target:\n    if target_value == 1:\n        target_1 += 1\nprint(\"Số câu hỏi trong tệp train:\", len(target))\nprint(\"Số câu hỏi được gán nhãn là 1:\", target_1)\nmyLabels = [\"insincere question\", \"sincere question\"]\nmyCounts = [target_1, len(target) - target_1]\nplt.pie(myCounts, labels = myLabels, autopct='%1.1f%%', shadow=True, startangle=90)\nplt.axis('equal')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:11:59.436598Z","iopub.execute_input":"2022-01-07T17:11:59.436844Z","iopub.status.idle":"2022-01-07T17:11:59.776793Z","shell.execute_reply.started":"2022-01-07T17:11:59.436812Z","shell.execute_reply":"2022-01-07T17:11:59.776145Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Đánh giá: dữ liệu có sự chênh lệch lớn giữa câu chân thành và không chân thành với tỉ lệ 1:15. VIệc này ảnh hưởng rất lớn đến độ chính xác của model. Vì vậy trong bài này em sử dụng f1 score để giúp cho sự chính xác của mô hình không bị ảnh hưởng","metadata":{}},{"cell_type":"markdown","source":"# F1_score\nF1 score là trung bình điều hòa giữa precision và recall\n\nPrecision được định nghĩa là tỉ lệ số điểm Positive mô hình dự đoán đúng trên tổng số điểm mô hình dự đoán là Positive.Precision cầng cao tức là số điểm dự đoán positve càng đúng không bị nhầm lẫn\n\nRecall được định nghĩa là tỉ lệ số điểm Positive mô hình dự đoán đúng trên tổng số điểm thật sự là Positive (hay tổng số điểm được gán nhãn là Positive ban đầu). Recall càng cao tức là số lượng điểm positive bị bỏ lở càng ít.\n\n$$Precision = \\frac{TP}{TP+FP}$$\n$$Recall = \\frac{TP}{TP+FN}$$\n$$F1 = \\frac{2}{Recall^{-1} + Precision^{-1}}$$","metadata":{}},{"cell_type":"markdown","source":"Để đánh giá được 1 câu có chân thành hay không, thống kê những từ hay xuất hiện trong mỗi loại câu này từ đó biết được các mối liên hệ của chúng đối với câu\nWordCloud là kỹ thuật trực quan hóa dữ liệu sử dụng để biểu dẫn văn bản. Trong đó kích thước của từ cho biết tần xuất xuất hiện và độ quan trọng của nó.\n","metadata":{}},{"cell_type":"code","source":"from wordcloud import WordCloud, STOPWORDS\nprint('Ảnh word cloud được tạo từ những câu hỏi chân thành:')\nsincere_wordcloud = WordCloud(width=600, height=400, background_color ='black', min_font_size = 10).generate(str(train_df[train_df['target'] == 0][\"question_text\"]))\n#Positive Word cloud\nplt.figure(figsize=(15,6), facecolor=None)\nplt.imshow(sincere_wordcloud)\nplt.axis(\"off\")\nplt.tight_layout(pad=0)\nplt.show();","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:11:59.777983Z","iopub.execute_input":"2022-01-07T17:11:59.778671Z","iopub.status.idle":"2022-01-07T17:12:00.439931Z","shell.execute_reply.started":"2022-01-07T17:11:59.778636Z","shell.execute_reply":"2022-01-07T17:12:00.439212Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print('Ảnh word cloud được tạo từ những câu hỏi thiếu chân thành:')\ninsincere_wordcloud = WordCloud(width=600, height=400, background_color ='white', min_font_size = 10).generate(str(train_df[train_df['target'] == 1][\"question_text\"]))\n#Positive Word cloud\nplt.figure(figsize=(15,6), facecolor=None)\nplt.imshow(insincere_wordcloud)\nplt.axis(\"off\")\nplt.tight_layout(pad=0)\nplt.show();","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:12:00.440912Z","iopub.execute_input":"2022-01-07T17:12:00.441178Z","iopub.status.idle":"2022-01-07T17:12:00.969651Z","shell.execute_reply.started":"2022-01-07T17:12:00.44114Z","shell.execute_reply":"2022-01-07T17:12:00.968981Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Nhận xét: \nTrong phần các câu thiếu chân thành ta thấy chúng chủ yếu tập trung các vấn đề là phân biệt màu da,quốc gia: black-white,united-indian nhân vật chính trị:trump, hay phân biệt ","metadata":{}},{"cell_type":"markdown","source":"# Tiền xử lí dữ liệu","metadata":{}},{"cell_type":"markdown","source":"Ta nhận thấy dữ liệu còn khá phức tạp và có cả những dữ liệu dư thừa. Chúng ta cần xử lí qua chúng bằng cách: \n\nloại bỏ các công thức toán học, đường dẫn\n\nchuẩn hóa các từ viết tắt-> dạng đầy đủ\n\nsửa lỗi chính tả 1 vài từ \n\nXóa bỏ các kí tự đặc biệt","metadata":{}},{"cell_type":"markdown","source":"# Xóa ký tự đặc biệt\nVề cơ bản những kí tự đặc biệt này không có ý nghĩa, tránh việc dư thừa ta thực hiện xóa bỏ chúng","metadata":{}},{"cell_type":"code","source":"punctuation_list =[',', '.', '\"', ':', ')', '(', '-', '!', '?', '|', ';', \"'\", '$', '&', '/', '[', ']', '>', '%', '=', '#', '*', '+', '\\\\', \n        '•', '~', '@', '£', '·', '_', '{', '}', '©', '^', '®', '`', '<', '→', '°', '€', '™', '›', '♥', '←', '×', '§', '″', '′', \n        '█', '…', '“', '★', '”', '–', '●', '►', '−', '¢', '¬', '░', '¡', '¶', '↑', '±', '¿', '▾', '═', '¦', '║', '―', '¥', '▓', \n        '—', '‹', '─', '▒', '：', '⊕', '▼', '▪', '†', '■', '’', '▀', '¨', '▄', '♫', '☆', '¯', '♦', '¤', '▲', '¸', '⋅', '‘', '∞', \n        '∙', '）', '↓', '、', '│', '（', '»', '，', '♪', '╩', '╚', '・', '╦', '╣', '╔', '╗', '▬', '❤', '≤', '‡', '√', '◄', '━', \n        '⇒', '▶', '≥', '╝', '♡', '◊', '。', '✈', '≡', '☺', '✔', '↵', '≈', '✓', '♣', '☎', '℃', '◦', '└', '‟', '～', '！', '○', \n        '◆', '№', '♠', '▌', '✿', '▸', '⁄', '□', '❖', '✦', '．', '÷', '｜', '┃', '／', '￥', '╠', '↩', '✭', '▐', '☼', '☻', '┐', \n        '├', '«', '∼', '┌', '℉', '☮', '฿', '≦', '♬', '✧', '〉', '－', '⌂', '✖', '･', '◕', '※', '‖', '◀', '‰', '\\x97', '↺', \n        '∆', '┘', '┬', '╬', '،', '⌘', '⊂', '＞', '〈', '⎙', '？', '☠', '⇐', '▫', '∗', '∈', '≠', '♀', '♔', '˚', '℗', '┗', '＊', \n        '┼', '❀', '＆', '∩', '♂', '‿', '∑', '‣', '➜', '┛', '⇓', '☯', '⊖', '☀', '┳', '；', '∇', '⇑', '✰', '◇', '♯', '☞', '´', \n        '↔', '┏', '｡', '◘', '∂', '✌', '♭', '┣', '┴', '┓', '✨', '\\xa0', '˜', '❥', '┫', '℠', '✒', '［', '∫', '\\x93', '≧', '］', \n        '\\x94', '∀', '♛', '\\x96', '∨', '◎', '↻', '⇩', '＜', '≫', '✩', '✪', '♕', '؟', '₤', '☛', '╮', '␊', '＋', '┈', '％', \n        '╋', '▽', '⇨', '┻', '⊗', '￡', '।', '▂', '✯', '▇', '＿', '➤', '✞', '＝', '▷', '△', '◙', '▅', '✝', '∧', '␉', '☭', \n        '┊', '╯', '☾', '➔', '∴', '\\x92', '▃', '↳', '＾', '׳', '➢', '╭', '➡', '＠', '⊙', '☢', '˝', '∏', '„', '∥', '❝', '☐', \n        '▆', '╱', '⋙', '๏', '☁', '⇔', '▔', '\\x91', '➚', '◡', '╰', '\\x85', '♢', '˙', '۞', '✘', '✮', '☑', '⋆', 'ⓘ', '❒', \n        '☣', '✉', '⌊', '➠', '∣', '❑', '◢', 'ⓒ', '\\x80', '〒', '∕', '▮', '⦿', '✫', '✚', '⋯', '♩', '☂', '❞', '‗', '܂', '☜', \n        '‾', '✜', '╲', '∘', '⟩', '＼', '⟨', '·', '✗', '♚', '∅', 'ⓔ', '◣', '͡', '‛', '❦', '◠', '✄', '❄', '∃', '␣', '≪', '｢', \n        '≅', '◯', '☽', '∎', '｣', '❧', '̅', 'ⓐ', '↘', '⚓', '▣', '˘', '∪', '⇢', '✍', '⊥', '＃', '⎯', '↠', '۩', '☰', '◥', \n        '⊆', '✽', '⚡', '↪', '❁', '☹', '◼', '☃', '◤', '❏', 'ⓢ', '⊱', '➝', '̣', '✡', '∠', '｀', '▴', '┤', '∝', '♏', 'ⓐ', \n        '✎', ';', '␤', '＇', '❣', '✂', '✤', 'ⓞ', '☪', '✴', '⌒', '˛', '♒', '＄', '✶', '▻', 'ⓔ', '◌', '◈', '❚', '❂', '￦', \n        '◉', '╜', '̃', '✱', '╖', '❉', 'ⓡ', '↗', 'ⓣ', '♻', '➽', '׀', '✲', '✬', '☉', '▉', '≒', '☥', '⌐', '♨', '✕', 'ⓝ', \n        '⊰', '❘', '＂', '⇧', '̵', '➪', '▁', '▏', '⊃', 'ⓛ', '‚', '♰', '́', '✏', '⏑', '̶', 'ⓢ', '⩾', '￠', '❍', '≃', '⋰', '♋', \n        '､', '̂', '❋', '✳', 'ⓤ', '╤', '▕', '⌣', '✸', '℮', '⁺', '▨', '╨', 'ⓥ', '♈', '❃', '☝', '✻', '⊇', '≻', '♘', '♞', \n        '◂', '✟', '⌠', '✠', '☚', '✥', '❊', 'ⓒ', '⌈', '❅', 'ⓡ', '♧', 'ⓞ', '▭', '❱', 'ⓣ', '∟', '☕', '♺', '∵', '⍝', 'ⓑ', \n        '✵', '✣', '٭', '♆', 'ⓘ', '∶', '⚜', '◞', '்', '✹', '➥', '↕', '̳', '∷', '✋', '➧', '∋', '̿', 'ͧ', '┅', '⥤', '⬆', '⋱', \n        '☄', '↖', '⋮', '۔', '♌', 'ⓛ', '╕', '♓', '❯', '♍', '▋', '✺', '⭐', '✾', '♊', '➣', '▿', 'ⓑ', '♉', '⏠', '◾', '▹', \n        '⩽', '↦', '╥', '⍵', '⌋', '։', '➨', '∮', '⇥', 'ⓗ', 'ⓓ', '⁻', '⎝', '⌥', '⌉', '◔', '◑', '✼', '♎', '♐', '╪', '⊚', \n        '☒', '⇤', 'ⓜ', '⎠', '◐', '⚠', '╞', '◗', '⎕', 'ⓨ', '☟', 'ⓟ', '♟', '❈', '↬', 'ⓓ', '◻', '♮', '❙', '♤', '∉', '؛', \n        '⁂', 'ⓝ', '־', '♑', '╫', '╓', '╳', '⬅', '☔', '☸', '┄', '╧', '׃', '⎢', '❆', '⋄', '⚫', '̏', '☏', '➞', '͂', '␙', \n        'ⓤ', '◟', '̊', '⚐', '✙', '↙', '̾', '℘', '✷', '⍺', '❌', '⊢', '▵', '✅', 'ⓖ', '☨', '▰', '╡', 'ⓜ', '☤', '∽', '╘', \n        '˹', '↨', '♙', '⬇', '♱', '⌡', '⠀', '╛', '❕', '┉', 'ⓟ', '̀', '♖', 'ⓚ', '┆', '⎜', '◜', '⚾', '⤴', '✇', '╟', '⎛', \n        '☩', '➲', '➟', 'ⓥ', 'ⓗ', '⏝', '◃', '╢', '↯', '✆', '˃', '⍴', '❇', '⚽', '╒', '̸', '♜', '☓', '➳', '⇄', '☬', '⚑', \n        '✐', '⌃', '◅', '▢', '❐', '∊', '☈', '॥', '⎮', '▩', 'ு', '⊹', '‵', '␔', '☊', '➸', '̌', '☿', '⇉', '⊳', '╙', 'ⓦ', \n        '⇣', '｛', '̄', '↝', '⎟', '▍', '❗', '״', '΄', '▞', '◁', '⛄', '⇝', '⎪', '♁', '⇠', '☇', '✊', 'ி', '｝', '⭕', '➘', \n        '⁀', '☙', '❛', '❓', '⟲', '⇀', '≲', 'ⓕ', '⎥', '\\u06dd', 'ͤ', '₋', '̱', '̎', '♝', '≳', '▙', '➭', '܀', 'ⓖ', '⇛', '▊', \n        '⇗', '̷', '⇱', '℅', 'ⓧ', '⚛', '̐', '̕', '⇌', '␀', '≌', 'ⓦ', '⊤', '̓', '☦', 'ⓕ', '▜', '➙', 'ⓨ', '⌨', '◮', '☷', \n        '◍', 'ⓚ', '≔', '⏩', '⍳', '℞', '┋', '˻', '▚', '≺', 'ْ', '▟', '➻', '̪', '⏪', '̉', '⎞', '┇', '⍟', '⇪', '▎', '⇦', '␝', \n        '⤷', '≖', '⟶', '♗', '̴', '♄', 'ͨ', '̈', '❜', '̡', '▛', '✁', '➩', 'ா', '˂', '↥', '⏎', '⎷', '̲', '➖', '↲', '⩵', '̗', '❢', \n        '≎', '⚔', '⇇', '̑', '⊿', '̖', '☍', '➹', '⥊', '⁁', '✢']","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:12:00.971221Z","iopub.execute_input":"2022-01-07T17:12:00.971623Z","iopub.status.idle":"2022-01-07T17:12:01.006918Z","shell.execute_reply.started":"2022-01-07T17:12:00.971587Z","shell.execute_reply":"2022-01-07T17:12:01.006104Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def remove_punctuation(text):\n    for punctuation in punctuation_list:\n        if punctuation in text:\n            text = text.replace(punctuation, '{}' .format(punctuation))\n    return text","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:12:01.008127Z","iopub.execute_input":"2022-01-07T17:12:01.008569Z","iopub.status.idle":"2022-01-07T17:12:01.020952Z","shell.execute_reply.started":"2022-01-07T17:12:01.008532Z","shell.execute_reply":"2022-01-07T17:12:01.020149Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Xóa số","metadata":{}},{"cell_type":"code","source":"def clean_numbers(text):\n    if bool(re.search(r'\\d', 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":"2022-01-07T17:12:01.022462Z","iopub.execute_input":"2022-01-07T17:12:01.022813Z","iopub.status.idle":"2022-01-07T17:12:01.030146Z","shell.execute_reply.started":"2022-01-07T17:12:01.022775Z","shell.execute_reply":"2022-01-07T17:12:01.029413Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Sửa lỗi chính tả\ntừ dữ liệu ta thấy trong đây có cả Anh-Anh và Anh-Mỹ. hay lỗi chính tả. Để embedding word có độ phủ cao ta cần sửa các lỗi nhỏ này đưa chúng về 1 chuẩn chung qua đó độ phủ vocab sẽ cao hơn","metadata":{}},{"cell_type":"code","source":"mispell_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',}","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:12:01.031222Z","iopub.execute_input":"2022-01-07T17:12:01.03194Z","iopub.status.idle":"2022-01-07T17:12:01.048995Z","shell.execute_reply.started":"2022-01-07T17:12:01.031848Z","shell.execute_reply":"2022-01-07T17:12:01.048201Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import re\ndef get_misspelled_dict_and_regex(mispell_dict):\n    mispell_re = re.compile('(%s)' % '|'.join(mispell_dict.keys()))\n    return mispell_dict, mispell_re\n\nmispellings, mispellings_re = get_misspelled_dict_and_regex(mispell_dict)\ndef replace_typical_misspell(text):\n    def replace(match):\n        return mispellings[match.group(0)]\n    return mispellings_re.sub(replace, text)","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:12:01.050117Z","iopub.execute_input":"2022-01-07T17:12:01.050358Z","iopub.status.idle":"2022-01-07T17:12:01.065769Z","shell.execute_reply.started":"2022-01-07T17:12:01.050323Z","shell.execute_reply":"2022-01-07T17:12:01.064962Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Chuẩn hóa các từ viết tắt ","metadata":{}},{"cell_type":"code","source":"contraction_dict = {\n    \"ain't\": \"is not\", \n    \"aren't\": \"are not\",\n    \"can't\": \"cannot\", \n    \"'cause\": \"because\", \n    \"could've\": \"could have\", \n    \"couldn't\": \"could not\", \n    \"didn't\": \"did not\",  \n    \"doesn't\": \"does not\", \n    \"don't\": \"do not\", \n    \"hadn't\": \"had not\", \n    \"hasn't\": \"has not\", \n    \"haven't\": \"have not\", \n    \"he'd\": \"he would\",\n    \"he'll\": \"he will\", \n    \"he's\": \"he is\", \n    \"how'd\": \"how did\", \n    \"how'd'y\": \"how do you\", \n    \"how'll\": \"how will\", \n    \"how's\": \"how is\",  \n    \"I'd\": \"I would\", \n    \"I'd've\": \"I would have\",\n    \"I'll\": \"I will\", \n    \"I'll've\": \"I will have\",\n    \"I'm\": \"I am\", \n    \"I've\": \"I have\", \n    \"i'd\": \"i would\", \n    \"i'd've\": \"i would have\", \n    \"i'll\": \"i will\",  \n    \"i'll've\": \"i will have\",\n    \"i'm\": \"i am\", \n    \"i've\": \"i have\", \n    \"isn't\": \"is not\", \n    \"it'd\": \"it would\", \n    \"it'd've\": \"it would have\", \n    \"it'll\": \"it will\", \n    \"it'll've\": \"it will have\",\n    \"it's\": \"it is\", \n    \"let's\": \"let us\", \n    \"ma'am\": \"madam\", \n    \"mayn't\": \"may not\", \n    \"might've\": \"might have\",\n    \"mightn't\": \"might not\",\n    \"mightn't've\": \"might not have\", \n    \"must've\": \"must have\", \n    \"mustn't\": \"must not\", \n    \"mustn't've\": \"must not have\", \n    \"needn't\": \"need not\", \n    \"needn't've\": \"need not have\",\n    \"o'clock\": \"of the clock\", \n    \"oughtn't\": \"ought not\", \n    \"oughtn't've\": \"ought not have\", \n    \"shan't\": \"shall not\", \n    \"sha'n't\": \"shall not\", \"shan't've\": \"shall not have\", \n    \"she'd\": \"she would\", \"she'd've\": \"she would have\", \n    \"she'll\": \"she will\", \"she'll've\": \"she will have\", \n    \"she's\": \"she is\", \"should've\": \"should have\", \n    \"shouldn't\": \"should not\", \"shouldn't've\": \"should not have\", \n    \"so've\": \"so have\",\"so's\": \"so as\", \"this's\": \"this is\",\n    \"that'd\": \"that would\", \"that'd've\": \"that would have\", \n    \"that's\": \"that is\", \"there'd\": \"there would\", \n    \"there'd've\": \"there would have\", \"there's\": \"there is\", \n    \"here's\": \"here is\",\"they'd\": \"they would\", \"they'd've\": \"they would have\", \n    \"they'll\": \"they will\", \"they'll've\": \"they will have\", \n    \"they're\": \"they are\", \"they've\": \"they have\", \n    \"to've\": \"to have\", \"wasn't\": \"was not\", \n    \"we'd\": \"we would\", \"we'd've\": \"we would have\", \n    \"we'll\": \"we will\", \"we'll've\": \"we will have\", \n    \"we're\": \"we are\", \"we've\": \"we have\", \n    \"weren't\": \"were not\", \"what'll\": \"what will\", \n    \"what'll've\": \"what will have\", \"what're\": \"what are\",  \n    \"what's\": \"what is\", \"what've\": \"what have\", \"when's\": \"when is\", \n    \"when've\": \"when have\", \"where'd\": \"where did\", \"where's\": \"where is\", \n    \"where've\": \"where have\", \"who'll\": \"who will\", \"who'll've\": \"who will have\", \n    \"who's\": \"who is\", \"who've\": \"who have\", \"why's\": \"why is\", \"why've\": \"why have\", \n    \"will've\": \"will have\", \"won't\": \"will not\", \"won't've\": \"will not have\", \n    \"would've\": \"would have\", \"wouldn't\": \"would not\", \"wouldn't've\": \"would not have\", \n    \"y'all\": \"you all\", \"y'all'd\": \"you all would\",\"y'all'd've\": \"you all would have\",\n    \"y'all're\": \"you all are\",\"y'all've\": \"you all have\",\"you'd\": \"you would\", \n    \"you'd've\": \"you would have\", \"you'll\": \"you will\", \"you'll've\": \"you will have\", \n    \"you're\": \"you are\", \"you've\": \"you have\"}","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:12:01.068735Z","iopub.execute_input":"2022-01-07T17:12:01.06894Z","iopub.status.idle":"2022-01-07T17:12:01.085382Z","shell.execute_reply.started":"2022-01-07T17:12:01.068917Z","shell.execute_reply":"2022-01-07T17:12:01.08465Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def get_contractions_dict_and_regex(contraction_dict):\n    contraction_re = re.compile('(%s)' % '|'.join(contraction_dict.keys()))\n    return contraction_dict, contraction_re\n\ncontractions, contractions_re = get_contractions_dict_and_regex(contraction_dict)\n\ndef replace_contractions(text):\n    def replace(match):\n        return contractions[match.group(0)]\n    return contractions_re.sub(replace, text)","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:12:01.089122Z","iopub.execute_input":"2022-01-07T17:12:01.09001Z","iopub.status.idle":"2022-01-07T17:12:01.098836Z","shell.execute_reply.started":"2022-01-07T17:12:01.089972Z","shell.execute_reply":"2022-01-07T17:12:01.098212Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def clean_questions(x):\n    x = x.lower()\n    x = remove_punctuation(x)\n    x = clean_numbers(x)\n    x = replace_typical_misspell(x)\n#     x = remove_stopwords(x)\n    x = replace_contractions(x)\n    x = x.replace(\"'\",\"\")\n    return x","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:12:01.100098Z","iopub.execute_input":"2022-01-07T17:12:01.100433Z","iopub.status.idle":"2022-01-07T17:12:01.107619Z","shell.execute_reply.started":"2022-01-07T17:12:01.100373Z","shell.execute_reply":"2022-01-07T17:12:01.106887Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_df['question_text'] = train_df['question_text'].apply(lambda x: clean_questions(x))\ntest_df['question_text'] = test_df['question_text'].apply(lambda x: clean_questions(x))","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:12:01.108567Z","iopub.execute_input":"2022-01-07T17:12:01.108782Z","iopub.status.idle":"2022-01-07T17:14:35.818631Z","shell.execute_reply.started":"2022-01-07T17:12:01.108745Z","shell.execute_reply":"2022-01-07T17:14:35.817854Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Sau khi clean question, điều chúng ta cần làm đó là vector hóa text để máy tính có thể hiểu và học được nghĩa của từ, ở đây ta có sẵn các tool embedding convert word thành matrix số thực. Các từ khi được nhúng vào chiều không gian vẫn sẽ giữ được quan hệ ngữ nghĩa giữa các từ với 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tXTOzf2dvJxtSIZ2Rq5eQbOmjqqlMvMwQSVStHU60QFac8+WPFt306etpbmZtb2nuHRn63+tiLpGKJCoXGBgjkvyy8ERwAasCsef4kAFCh4PGhK6XNX62K/WN3CgCAomfZbeZgY12lClcrpfzkv/745bt+nXwcrc1MLR28O0RMWbHvXiJfpmwQaqH0wdE9m9av3XklTSRIPLt8RHtna0s7n7BxS0+/KgSgNnU7ggBUXpF8ZducfsHutuZmtu5BEZOWH32QWC5XfX42QEWZr85v3XDg7odCQssuf37uj81r1+y6lVEbqgHHMZW0PP1N1KY5I7v6O1ubm1nauAT2Gv3D79cTCgQNQ+4o+QkPDqz/ZfWabadfpfEVipLoc5u/69/JzcbMxNzWLSBs8rK9f6UIFGqswbwmKYm/vHPxyB7tHK1NjU0sHH1Ch85Ye+ZldjMRKDClRJjz5sKGOcM7+7rYWJia27oFh41asvvKu9xKJQqtDRAIpC0ynlR9hgHgNSvYNi6FNaL9UZLmlZWnV3BnE0J0Vq89iRmEEzBpuOZdVCj59Cjx7zeZ3qGPu/bghk572Sb6LC4R0lKqRLFWG0vo3v4WNKR2piLc+Fi+wUGhIZrVO/b44uPEXGntDJd7a/8TzRUGFo69h9VrQ7OLdRK5aS+Q1i8VSEYdhk1f/uveI39uH2WF4xiKKhVyqURcVVUpEuVmVyi0MS4wFGtcNtUvxL+TO7uupcQXQvMePdxI882JhB8fprR98YIzbEMGfrt0y5+Xz65sb0DFMVRNNEkkqqwUlhYWF5UrtC3C4YbjV143QhqQsTWIhACAUK1G30x7OFfzszbvMO9s49Dl2LsVrgAAmr73qleph3sTT4NDxOrb5brXVCZdmhdqUDPeZBqdTqfWPcD6wTPOfyjTif8qPBemkZ0kQ7sxZ3XLUVdl3PllkJNuOdQaRyqmy9Bt9zIlbQhjLr7zY3874vbAXXEiJdb6O1F5RcKNdeGWOg2h1aZp44bMPRKXL1LXhqaVlz3Z4K61vg6a+euv09oTh8zIVFpdSiCnb05nVZW9PDDVQ2twpFLrztqZ9d31LF+O6qT4kPPjzv4UYlxbO1UznDrmsqD5F7PrIgoLnx2eSxgo6X1Wn8/SyTqhFGbf2zzCtq4YGq22FJbXd/seZlcqMQw+ChDIfxbi+S04FUn4QrIdw7dnNXdl1f0x2vOcxt4r4+ru1YhdUfbNjaPsyXWCok7sUmxHbriZXS97RMxUR0LUd9746wAimiSJQlxO8hq0IRWvODmvD1GP4YSta8Z6a3OLkai02hIZvhN/e1Ws+Ey/5DlRa7o2nsqpo67wlSgR51styo89Mq9zTU5PhEqj02rnHLOwNTcTK3SkKi54f2C6VqB3+HH73lXDtVG2SFRa3U2A4j7r+CeZzuCWvtw1qCb7MolC0xHD7C4LTqdKGn4Z0uK4A1MDqDU7HJom1UwCZJteay6+0409DoFAIJ/RRT/sHhZIbIk7Lo8ukLRdX8NEuU8XmBNKX/vhez9hTc0gZUdDCYFl7DTpnFYhLzyxaAARZpEz8VSssKHWjZbGnZ9IfGwQuehqrvbNuFleFsQ0ZLn0nbxxP2K3TfYjZgOHXx6WSqubUfHyB1NCu/fsuSJJ5+qPa/s6EKe0zWY/rEKxhhMelnF0UW+t5Lefcya9UitU0aTtAcRUwPEcsKdIe7lKUl6cm5WVlZXdgFxNGzBB9MnpRD/0By8/nf/lszCGoUoRvzA7PfnDm8dXju/ZsHTu+AHdPEx1YlGazIiumS/E2c9XeBBv2gzYeKsEr59HBMNxZcGpDsQXYuU37iaRWiP33LIwYkWgN+5ockX1WgqVxC20Ir5Zh/ar4xsPuaJS06SUj28fXT62Z/2yueMGdvUwZ9a2iNx56e1UKcw6AbNO/BtGGECmGbn3izTedbw4J/nl85JRo+rl3sWTL55LBwBh2g0a7kFp+sSQ4MmKkaN3fVQBQDN18/Vwc3e3NSTLyvPSP8UnZOTxJZVv9q/YH+K7cbybfkv2QmnataUTp+15zQc0nr2zg72bp5ulHlpZkJKQkpmVXpB2eckkvujAkZ8GOP6zCWBxWeqNVcOH70oCCINn6+rh4uzsZMFSl+RkpKckpeaUvNz1zZAy2dXd3/oZ0bQ6LplKSFBa1bPj25/jIgOPLj39XG0MVLkf4968TSxVYhlHpk0zmVy6+VCamVcXf3dXRxNlcUb8m7fJRUJFye35qy70vDTLw4CGEHtoha8Pzhr/62s1oHFMbD39fdwcrAyo0pKM1NTkj59yK9VYzG8TfujS9fwwkxbt2Pl31o0atDUaBxRDG1d3F0dnZzsuJsjLTElKSsstSjg4cxRfem7vzG5mTJicHgL5j2544ThAzPstGmty83iZpDTl4tl3835qR258YdH136MEmvW4sdfk79pV72ppHnxZ1uU1U6dveyjAqDxbJ0cHd083Ky4Q5WvFbl7u+eUTy4X7Dq0eYV+dkJxEYzKpQKiKXfuTTMpzCgwI8rMlFbxNQjv3HeoC1C+qfQIqo5b8LMZIhvbebl7+fnbMyoy4uI9p6YVV8cdXzKHQj/823ZPTQr9ohlaeAQ7ZhZX84gopADQze3sjBmbgbKhZueNAWR5/fPGI2WczAZVtbuvi4e7iaGdKERdmpGekJqXklfz1c+SQ0ovXtgxzZdTsDFJohI7F5l9a92OxErH2DPby8bY3pgizP35KSkvK5KvUyUeXznPzvzfPhxjA0ntrF228lq0AFJ6zl59/gJsFS12c+PbNu085Qsmz/UtX2Lgc/z6odjLCy9/smDxo+Z0SgLAtXN2c7V3cnIzJ4tKslMTk9OzcvAc/f/Od6I+Dy4f760OVBAKBfFY5BwjJxJynbwCADJSmFUmVGGCRW74JQ9U4Qq4L0oijyio+cbyAwWRyiGyS9fIMIcQ2oikTABmmxuRCCQC8v9dsGptBaq4/oI1HPyhMGrnBhAcAgjh27xQcaHbvYQnIPnklZka4vZcRWZV67o84zfzENfIZPtxce3nZ010/LvvjfimlfjEkmmGfvS/2hTP1eLaWAJQDcVFFRYUMWDE/841gKEYEqqynM+PqyozYh+cO7Dp4/nGOVLcapqERUywUN+eLTdJncgxYDRwpNC+pesZUAFSYEhULxABw2/4lKAQZ7+4d37fv6IUnuTLd8WPo6etj0koxDM4APRr+RY8GiuW4RypV9skJmlWrbfjcG0X1jWKf1rqQyACh+q78qJYk7+7ZhEdD4taeWp8ouv3g/e90d3lK76wf7ap9dK1n3kgSYC14NMiS9n0TqHmgyKYBY9ffzdDZ8pKlnP15mAsh/cy6zLuarmirR4Pv+rup2flNkpdXVCGS6Vps5RkniMS6JIZlhyk77ubrfFby+sj0Xk5MqkYAhv/2rtosK+c/3+Jf8xhz241d/yiv1nsjeUcfq1oZQrXrsfxSUu1nGRcXdbLSmioC9ydUECeLMZU4+9gwrUuEYdCEne9EOi0rfPBTF0vtDhkn4qyoRY+G3HPjTQj12ixg6K/XU3UcHariTi/t526gqRjpsOllsQp6NUAg/12fBgzHcOnr5Z6EDLDo8cMDSRNXZW7tyCYULLNRWpFb/dDLE47N9TXUfGLmO/zXa8k6fmeqxKh1gz2IbRSjwMVnkmpkSO3OFQC8DqsfaQU4WpYZE5eP43jBn3O0Hg2EmHLqv/FObk2Big8nF4WYExKPF/zD6cSW5DimlomF/PS7v4wLIES43eITD1NzCwoFchTDMXVV9LaemvdpHLc+c46/Kau7UZ17a8uEQFPCaGs46HROjfgWxh+eW+MrRzbq9O32Z4V1zgXFj7dHWhH10K17//RE29PMI9PaEbtd1JAVz+qmu/IbS0MJ4wXiHPH9o7pk58K7C9sTvgwst/AFp+IqdAYy//aWqUFmhFT3/O5yQoUa/mohEEhrUH3YMFLr0uC0+lme4rPKWtmbqAsXr919/OZTnkQj4VBh+o0JhAsar+vEE9lN3iOMGkzUYOg45s+C1nk0nBvPa86jwWF9krJJjwZfrUfDqjZ4NFgvfi5BsYYTnkYXv/N9pDYdPyVy7xshistiVxDZnUkGTkMvCmouzrkwO8JYmxFDFwpDf3CURoMufnNyLLGzatR/6a2czw6uJCPm4aWzl+89fZteJlZVX67IurW6h1HNOt7A3M7Fwy+oU/defUdOW75jzXAHE0ZzHg1k31F7XosbV6MsvR6pmUsQU+8hZ0q+wKNBmnhhaacaF3OWobk90aRu4QNGT1288vup4dbQowF6NPzrUCjGHr37GJw4kZuc9DamMLJ/7ZkBkHDpUiZAEbL9kJFeZGVSU3a5yky+cZCvZ26x2HnJ9un+rOo4XgBBEJOIMSMiHtxMfSQC5QXlEjkKQHNfRunTS5cfx4oAMIlY+MfuHwMNdTLIMFxHrfiNqigas+llyYsHt+/F9pjZqU02voIbe1an8ChI4+ZjSoVe94lTR/f116uxBEbvWnWzEpBoxt3m/X5wQTAJ1HXItMPkfdvEWUOW38+sur9xX8ykfV3069luOQFDFy5d3N2aUtN2t5mLev5y70QlBgDdsNO3W9YNda/tluOwMd0P344tSFSCtPcFUtzdkHBoEBbLHD3dpGqToHFzZvpzdKq3CFu5oP3e6GtVSlxdmMEHoNkdQfX7PasvlAFA1m8387cTP3Zm6ZTCbTdmwzZp8bAlxxIrojf/8Wpy4ECtWg6BQP57Pg0IDnCG5/i5oZtnvlCUpj87+6gsLLK+t5My7vjBOLlmHW0zaPZgnjY8g+aZL39z7sq9eAEAvJ4/7Nm1qLN5tWUeIAigeAxeupOpLhr8S3R53N2b10b2dW+vX69Y4z6rlnbnEdnaScYOgcYNtqsQ5yk79/0UYV1TIs137MrN5ZmD50fxK2IfPryfOMDDn9P0xgBAyAy2PsPO2oijlU1UfTNrOxtLrV1WVf5i17qHKCAbufZd9tuuCa6gTr6RbfouPswqTxuwNVokuLruwLuR64Ma7AHywmb/umZ+Z4sa0Y4gZt3mb1xw8uYPcUBRJciIKwRd7YAiJ6tcRGQkc4rs58ut2WEEvO6zfp54ecJt3MzOTl8iBEA7c6Sd2XQhWQUA1XnctlM7NONfK3EpVn0Wb1CLymatv5qXePzYk8ndnEN4NPjLhUAgn3NpoLh08LC3oMdmKjKuP8meF2xJpbXkgsp/uHPG6NMldCOPyA23zk6zJyFkGteYDYAQyCSSSiEG7Bq5G2CSkiIZcWiOzDHmNhbGjXwQcFStkP9fbYkjxLCYdgoPDLx8Nztbrb55/GHeePeKYydzNH2gm4dM6GtQI631PfqMnM/yrkIo9QYNIXN83TRLeZ6lU7sOhqevCcrjPqWk5EfY2rQU0k+eeWPPgvlH4qlGHZYcPfJjXw8uGeCC55vmrHpUDsh0fc/wEQN7dPBzd7Kzs3d2cdAI+YwNpw/fygJ1M5QuqFghFckBYDd8X1pSpBleMoPOM9Vr+88m88q6VfteCTXDFDxwQES3jj5uTvZ29o5ODkYMoHh3eualQwCmjP7q62g4BC37ewDAtvboHcY7cSkvOSEmpqz/wBo1NeViVBaOAbLjsOFeCFrR5P2sTrPXbRuYl19QZdHTTjd5L7FBRKeyuQCIAKpQtRQKq/ztq/hkzeNoO27aQI8aK4OmJO0fqllQn7Hdf395T5b49uO7LEknX3Ybulj+6tqpV819SFV6hQ2sNTSo3p88p2kH3Shk9pxqK0N1h7SvfMeN8dn1MrtKXHzxQsL2LiG67WD6tgsI8qLV+CUTMV6d/C3AyUqA05lWfUcH1rosE1LQzFJPjwmAEsgrJGptrB8Kx3HMtmOd8opEJJ63H63BeJKMTBkIqQqgCCpXNt9fLP7c+QwUAKDfcf6CaitDvU64Dx/Sbs/d5IrC8kuXErZFmvJgwFQI5L9qagAIzrKLnD7E8MV5QV7G2+t3MiMnOOpcIHt86Gw6igJA8540uwu97tgE/0NM/IcUAID9iMkDfc1BQ7FLsvKLHNl7S/Q1yccPn+JTRO2DddVQkn//QKp2Ld1Us0hdZ83oYlZrDSEK1PfsOWGwY9ShTPTdu8TEdIm/P7sp00lNeWp1TcRaHFWr1QBol+eVsScvCgCg6Tt3nzbOFTSSb9Rus8e77IqNU6vSLlxMXR/kUa94g7DeHV0tdEU7DjDcJCjUEMQJgEotFRKuphSuHpNOB0AKcqJORHXiDQx1MSSyyzFMghf8tqcf2dLB3sHOrNoNOfXGzRQiC13g3MXVVoZ6EtckLKJru4u38hIVt259LB3Vnsejwh8uBAJpSbJrpAuzU3ig8+nbmWnSmKNn304K6GXFaj5kYebFC/EyBAB5OZ9jZUghDqGxjBxdEVCAywr5+WkFwM+mobooSn2RotXW9W3tqyU8qTpXgVqmRBtlTVbLJPx8Efg/tTTodYvo6HnudnaKFLw+d++98/vzORqpTTfrMak3i9CbNRq1vlf/KV79m7fjUM3s/XqGG187zy98dvdZ9KDONg7Nn54o//DqTWyyZpUgIOkzqwMZVb7YfyRTU7O+57gth/ZE1Dt5DmQZBSKtSQZrav1TWlpSUIwCowamcHHa63TNXwbH1MuF0eYBSr5+NSZfCADgdJu9/eDPofV2HbDiktJSwoAOc0dDQ8O/jZG1R9cw3qUL+XGfYhNKB3Y31f5go65myTEAnIaN8ERAE1G2NT9UKs/ahWft0q5aH5SVF+blFxQW5OdlZ2Wkf3pxN05QY85o/kcty0/LzyZSXlBybh/fnmRArv8EICREmhdfSQdABtJyC0v4GGC3YW1s3HnYQA8jShPSGVMquF2CnVi1b+S/eFFGAgBFlVXP9m5NVKsaCFkynZxTUknkhKl4EVcCQnQVep6Zsa0ZUmscIOqjsYlDvAiVZOVtXS0na/6hMGkkrYjRyiAcQUgUro17Oxt37XBiCrGgpCCvoKAwLzc7MzMt5e3jKm2L8JZS5he8ii4FmjaqpbEHthSgDb85Mp1cnFeuJGnmmOi4ElUPqPVCIP9ljZRMN+3yzSSb8zvzyrLi7t1IHjvPvVZ5qbhz8FYejgLADZ09xZdQsLRKpDwnKy83l5BE+Q/+/D1fn9xAF0IQRcm7CjoAEpBVWJBXjAVzdcQuz8ORW+cc0QifiEBTBqWuKOKPvom1dzAPZFZg6bkF+WWYP7vtNk4059kLIgubqjz34W/bYqvDeuvINyqeoc06gRS+fF8BPOodOra2NzHhIroGEk0HKCxjNgACgOGoNvME2aNLe2f7qwmJIlnMoRXfp9wM8G/XvkOnkJBgH2uPiOEeOtoqAoRxcUVyieYuLOHkxo2NdFUSlVzxJldGAUCliksslihceVRo3IVAIJ+3NIQMG9D+fHT6+8r0P1ft7u21eoAlvUmJi2Ze2nfkaXoVBgDJd/7c6kC5VJaRW49A8CgGFKV8iH6VN8zGpv7dpU+P3xIS6YgM/UKcte9RmTQqYdVV5JVJVOr6qyilqCDp+cev00Hki24ihqVjRBevE09T4sUg/tCmXwuKiSR6Vn0ndmPVzEqtKJxi3i6kf1+vyycShHeP/Xmxc7vZ4U6spu7DK5Nunjt1O14JALAaPrqHt43WAlCWmKQgAsYb+AyPMKv1V662GDy7nyioJAwNqKKJAHfihPef4rKUXs66Dm54+YvTN6sAAGw92669bNo8fNKcHIGMSHTtPHRYsDGoF5VDVZqS9Dq2knhThWIYBh8yaGj4l8ABIBtZe3bupXfhfGZswsdPJd17mgEAkqJu58gVAFgPG+FNauZ3XvNDl2c+uXz+2oOY5CKBSCisrKwUCiv4pQIpWs8S2RzickFVMXFpzs0jv90hN3ElkaNF80LEr1JIcVD2YO/hxzkVqnql4jjN1KXnmG97WNVrr9WAOasmerMoTfadxGBzarfV1IVJJYRBRFn+bPeqpr0gcJVcTjye/Gw+ADqGBjKLztJjNNNThMTg0Buo5XV5hJF6A4Qrq/JeXT0T9VdseiG/sqpSM5yCCn6ZQFYrFlpM91uUUgKI8DNVrw788hZpphNawcfP5isAYMGnAAL57wpwhEQz8xs1OXDn2tiqhPdPHsROdQ+ufqhzLhx7XqaRHBaD5g+x0rEzAClfKCwlpEDWvdM7H7YodiXlVVVVCgB01tBsYw65ebFOdbLiUnWLJLRDEpNtYG4KQAUQlQmrKpUAtH3DRlGYSGTxVIoz7uxccb/pIVES4g1D+bnl9aObUblMBpPaWErXxPfCAdBKWVbwmIUz3qetOpUoUOa/f3jh/cMbV2zsHRydXHxDe/ftF9HN15JVU0p5Bl9BTArou+NbPjap/uGoUkmMpCC/XKaCO0kQCOTzlgaNtHadOGfctWeZD/KqXu1eOIMi2/zjSHduAyEjTbu7b9naP2NL5QAAj2krv/HhamcGhGno2nVUKC3mhbL40ZWTZ8Pbz+vtUBvCVl1wc/3Ki+VEvBv7XuNCq+U714Knx6OBQiWIufIwdXywsSWrWqXG1fzke4d3X5d8le5VB2nEMLVS1VYDDMlncC/fI4/iUwVo0u0YrZJtP2RyMKUF63cTg2vs33PMuIFPV17Oyb27acly0q9rpvdy4dTblsRVlRk3d/2y7tCTCgCAUdfvxvf2NKvenGPqE8f/MLUi730W6OGg44+Xe3fX9qjYMrnWOiOWo42bUPno0vkr4aFze9dGuMcK7mxZdb4IAJK+cbvho3xaXtvStcOHozrDR2MzqVQyACgofJ/CV7hbMGqmYUyW8+L8gX1XirX/lSnVamhogIaGf3WQjJw9Q0P1zt/Ojv3wKaGipxkPZFy+nSVTAGA1dJhni9ogmnf553lrz73OyCsW6Tj0Iwxjr/a2Kn56albVZ2pXK5RKbWhUhMZk0imk5qwauFJO1+cyaWRQ/PTood0f8uS6Sh2OqpluXendv+1hVV/n5Rgamxi3FK63xgyJyaoUhKEBQchMNhtp0rUIYXMQANS4OZPUwJZAIlFILVgfkVbk6cVRUc6jbQu/P/gsu6xcpCt8GeY+YZ6K50/SFOhn1FRZlaK64ZpOkJrvBKZSm7PIMEADBPKf1kYJfdLIJWJS5ObYm9Kk968evJwQ3IvY0Uo+cfaDUIoBYDdpVk+9emex1HKlQl4tdhlMBo3UlNMZIXZVcpoBl0Wu/zGJ0pLooHMYlPorbuI/JDKFRlhAMJUa/TI1B5VWVreaRGFyWEiTR/LYHI0mTuGYNkxRRCKTkdbk2cEBMOn67cYzLh2OHT5y6urbEhUmq8hLqshLin3+5MHlYwcDhkxf+v2ETsYaia8QK1CtGkmis1iUJotH2BwAMIXcgEODIhcCgbRGthPxbfQ6zfx1+acRP5zOFGVe37kw8+Gl/mOG9+0S6GZtSFFU5CS9uX/lYtSNB7E5IhQATsii7Uv6WNBIhFYLEEC39ouc9t2p13vey9PvbFg4u2jWzImRHWwY4rSXUXu37L74QQQAieswYNHCHvRquzXdI8jdzpH6KVmFvto5cwG+bO7Y7p7GqtKMN3fPHz18+mGiiljJ/u1lB9dUD4AioCgtjX8cXWjuSCXTDXl6lNZNecB9YB+fPXfTBGVaB18EcRk9PpDUWjtDzeBSrXpN/n7Wh4z15z6Uf7i0buqHe72HDR/YO8Tf1UKPLCnLjn/119WLZ689TSgRAUC2Gzhn4aQwd1aNn4Bppz7O4HU6riyO+X3WEt7K7yI8jMlVeQmPrhw7ejLqeaaoeo6TllQ0ddoZzbqz/vv5/PlzJ/ZrZ6QqeH1l/6adpz5IAELnBk1ZNtbhM8NnQhz5lgvKPz54UWjrRgNUnrG+Z7CLgQkZFKClZxbNtZEuGhfmbkytzPv45NqZPw9ffJmtqL5dKJa1dAIbAg0N/8AoWTl7BnXm3r6V/TT+U5aoJ6/85p1soQIAy2HDvFpK+oLGbZv1w56bmZUadY9hE9A9NNDbw8PLx9fP29Na8XTd0kWfNzSQyGQyYSCkdPjp0OaR7a2oTR8e0khOEl3fzBKAjwwug8lkAF2lEUdRFoPLbGRQwDEMw3DQgnpXo3sj1SZChOU6I+r+EgdUgTZrmUBo+hZtGmIc/6ydAVdJss4tHr/6SglhmtS38+kQ2t7Xw8PL39/X1cGBm7jY/0VGKfoZCU+lk7UV2U859XiZF67CmjevUPQsuPDXD4H81y0NgGbg0mXsEOObZ/mZL98+elPcK9wcqKJPX0kr0azLA2ZNCeDU18FIFDKFmB3JIfN/3zyphzkNa07s4gjdwNioLd4HarkCbUKKY6haa1OmMuk0OvmLektlUABQImzjbkuvnJxqrZA1Lw9JNEOLLxxUTadZZr69J69qP2je6rTnNy9HXb1x50W6BKAifkEyv2BTdqUK/LZukj8dkOlk7TzEHb7//rqOvObLxACZY2rBhecmIBBIK6SddjXMDpi64xyFPmnun4mSooRXlzISHh7lsBg0MoKhSrmkUiiUECfIrHst2r3jxzB7DqI1KRM7aGQDt8ELNqZmzd5wK1OYeG/fsrfnNrFpJEwuFvDLxWoAqCY9Vx7aNqw2bi8A+p1Hjup1MybtaQkq+hS1fc6zo1wGBVcrJJUVVTgnYOQC66c7LxX/3c5ReR7t9UFKJRCkP/p5YOA6ix4/rN28eIA10sopz6rfiIAtD5PLBMQMgHhPHENkJm6lnaF2cKkWoXO3/I4jczddiBcUJN87uf3N9UNsJoNKRjC1QiYWCSvFKhwAjuOg7zf9unCAPatWnUdoXtPWjjk45kwBKsq+t2vB+zP6DCqCKWVVgjKh1DBi+kT+1Zvvi8tRkPI8VTzKpF70Y5qJEQMBlQk3f/8h+uQ6NgVXSoR8vkgJSGS3kdv2/hDCbJiMtH7ryYYewUbgUzmoyr+3YWjADrOIacs3rB5l1W/qmOC7aVeSRLLsK1vnvzjMZVAQVCUTC8oFKl5AryE2isdXnwlAQUJOKV8OjBjwKYOGhn8NqrWzV0Bn5q3bac8+ZRVIjR8/yhGKADAaOsynJTtD+ZVfj77OrsQBoPdYd+P4nA4GFDKZooFKJoFCFhkoa3TV5vfhmQZcjhEAhUBdLGcaWtnZfd6V32Nh1POZ6kaKMUKmMthfvl9EMbY3QpBKgOGCAtTcwubfjV2A47jw/R+rL5VoNFbHrot+P7ywpyUFRzTjSaWSEYBmKJXEriOOtxBZExjZ8UiEJluRrzS1smW2RqVG4CYbBPKftjSQTewDIkc7n92dnv0i5nV0bvggy0en/sovlQFA7rtwhBMNqa+DMQw4XB4AxQAtkjN4FrZ2X9PkKM8TyBp7LGBSUUURoZ9yTQ319OlfNFOZOGhajaswcTliYWbzWfEGAPIlCj5CGFhIdD0jcz0jMyunoEHTfxaXJt49vm/3/lMxZQArenr5ZlS//v49jAysDGhEBCFRnpxnZ2+PAChzIRDI1zM1kA0DJ//2OCh8x9oN+y69E1aVy6vK6ynRVoGjFq7+aUIPF1PimINWwGjvRUh6zhHL9p912PrT6kMP86r4hVX82tWu++Al27Yu6e3IRarNDNo77Ces30/hLF68626hRFpRLNXGgqdwfads37cooGjjw51/v2s0w+D5G4bemX2Zr1YIS4tBaUxKeoYCtMLQUD3lGUaODTG+nSjgqwAAQd+OJDIYt9rOUDe4CNOm6+LDNzuG7964ae9fqSIhXybUvYzMsgkZu3T5orG93PTJSK0LNPG9WAzddX0XacL3pxJUcmFxfvV9JDP/KRu2rJneMd0wffCOl0JF+bl9jzeE9tedYxG78CVTw0rPrNn/JK+gsqxmWnYbvfr3rXPDrJgtThM4ACROx4WbB9389moJKq8slVeWRqemZFUCK32vhfv2q0jT115NlkkqiiXVYfxp+l6T1m5bN833057v3z07m4u/vvTi0+iubnYc+JBBQ8O/N05WPl4BgYzbz1NfJqU+zLiXXSUCwGDAcO+WfobyuIfxAqFGn3RbsW9xmHX9KDWy4rKKIm2EUxRrwdCgZ2ljZm8IPgpAxu24nBk9PFgNLQ04qlKp1RiVyahOSkZh6hkwv65qqXnyHTq5M0iZKkwpiY56o+oR2tjSgCvFMoTFoJBIX19NxNUFz67la3RpS79+S5dEOjfoYf7HHIXWwoC15HVs38GNSXkrVqKy1+eiZYO6Nx4nXCWR4QwGVbsPBzVeCOR/wNKAGNi2Cxvnt3v1h7JX0bFxZV3TL0TnaXQw7sgF4ZYkBNRXWzg2Vha2xiCRD9IevMudFenCbSjqcUytUikxCovRdt+D5Hf5EgXKo9W7s7KkIPWtQKO5OVtZWBl/UV/pjiHuYF8xUIr5MTc+gY7ejS/BFCIZicvWSu8vEm5YVc6n2NcvX8XkmY+ZM9LfgkOhMzl0JocbMumXwJ4Rod+Fz7orA3nZufl5SmBk5uesz2YAoRy8Of+SP9HehNRYtMvlGIlKoVUfroMyFwKBtHI1rM3aQ2aY+A5de3bQyqrc2MePoz+mF1aIVSQmz8LRt2O3zgHORiwKqTqRTq2kr7kXQVjWQVN23h255NPTB49jEnMqVFRje/8eA/p1sOGSyWRidqgJ36O9Q8999IbrQ+Z/fHDrr7cpuUI1x86vW/+B3V30KQDgBwsUB4jQNpRqAe/327ucHcQ2P5naeM2F+M8/GDPnAPExpfaAMULhBk47+SHk/sWop+kVSpqRa89uDgAAz6XXUpZg1RcjLU15nIAQR9aZdCDEQdB3gx3bamfQHSAyy6rr5A1dJq0qSXz95GVMYlaRUKym6hlZOviEdu8a4MijkBAiF0ddvEetlYLG85955M2wH5/evPU8uVgM2ObuQV17dQ2wNaQjCGKx7nHJakJpJ1EaLCcwjGQUNH759KFT7ty4+/xDoZxh49t94IAujvp0YnlR+30A6+Frbg9ehRPe31QySdt/BEcMvCaejg++d+HSs5QyFdXIvWuEPWG8J5t1+en8u4lxD24+iE4tEpH0zZ18u0T07mjHJQEEWC4+kb7wWL3vgtbjcoU2BBxChqHhoaHhn0Lzo6M6+Xh5B9Cfv0y+d+vPyg8lVQDo9x/mq0duYeEuqRCjWs98c3vjhrnBK2Oev46OrYm5irWwCW8d5OPqZQieC0Ds7tNvRgQPdOfV12ylCdc2jhu+/hPLPvLHTVsWjPRoMbvsl+tw7JDxnZm3bovUspLLG48tvzHVrJH+vDGi15qX5aYuHacevbY2RO8rTicAqKtKiaxBVDrXxLKhfQBP/PNYgkobR0wtayF2Dr3jyFD2hStSqbr88tojWd1nNTrplXF4aJ/F93KpDsETj1zd1s0IPiMQyH9aF9XKcJazb+jAnvQPD0VPYuNuHiz9WFyAAmA3bWowkVmmwerW1tfTpZ3xnft8EH/o1KuRgXYBBvUlgST9rzVj+myJYzr0nr/t1x+HtDNofYsEF86+WRZuyTGoO7KmLk96e+1ipualbzt3NyfmZ4zCtbl7QD0rtUmX8cHg8Rsgz0uN2n/t+90DGx5VULxd4R26NZdtExQ248iFZd7kNo8lEMfsXj5t640MAKwp3bp7mHGYNQYCgDAMzFx9bcDdVEAik7R5g9r178A7/rqgUC6/veaPj4OX+zW0lBdeXz1mxq/PRMb+o3Zc3DHS0YAGDQ0QCKTVy2HtXxKJjDB5Tp2HOnUe2kiLJ4IygIZ2zNp7AcDJXCv/yEn+kS3VoXs3wjD36z/Fr3+DShAShdZA3SdRWkqkg5DIFFLjQ804ABSmpf/Aef4D69VAolDJrRHToOLpvWSxCAeA2mveIFuSTqjjLxlcYsJhWvj0GO3To1WDS7zENYtzloVPn6k+fRreQVgGaOTml10aeH59Jvr1qXcjUr8ipIlSCEsEQmGZeg+e7T24cUMRhlVQ/2lB/Rv1AUEafxdNfKGQtgGPQ7bmUdP85OnOvt5+QXSAPj8U9TGrCAesAaP9uCSkhRQHhjamDDphAYs+eStDpFKpMQxD1WqVQph8c//G7QeTqy8Uy1RoC5vwrhERIV2cNfWUnpj8/YE3eQKpQoWimrJUSknh+9v71q3/BACQKvXpHJ7eP2ZtAfqDV3xrTQYAUxT+9cPE9U8r1GqVGtV2ClULHq+Zv/dDIQYUxXl0H0f2166eauJEHCmWluVGX38nBQAjalap1PL8y/MnbImvqM6RI6+StjCa7H7LpjgzSABHFc8WD/35r2KVSlU9mmoUFcZs+WH36wwJUAnzqB72bKjxQiD/KzLc3qdTn8FGAIhf3fljz52sIgwA3/ljfTkNw9QSOo5Dt75dwh00AqD8yMwlB59lCKUKQtyhapVCUpJ0/cDKLXEAAJmKReaYGbStPZLL3y09m8wXEYIcVStE2dGXtq48xgcAGISGdw3zYX8ufQ6JSq0OSy4VaeYDgBKOcVTrIcsmmAAAVCVJ53+a8ee7SrVGsGEYiqpUamXxnYWT9+WjAFQVFDJ9HclfNA/oBXTx8bHRjFn+lo1nPxQI5TXTgEpalvr22uVUzZWOjg52thr9jBo6baK3LZEXLWXFoDlRWSKFQqltklqtrkqK2rT79LNSAGR8soMZm06FMhcCgfwNk0PTHyGfuRVpY1XI3y6k7Q1qQw3FUWdihQIUAM7o7/uaECvvf6BBn/mo+fe/cKRae1/T1xHV/u2RhbQVuFvbWi0VoTsHe/m601980MYlZfcZ7csjtfjbJAUO6mF5PqUwVyW/OzF8YsbP34V5GqGlqU+vHD14/FE+wuawUYlEjoOSYpEcbW73CgfAJHzON2PeJ2y+l6Gour0spPNf8+ZM6hPsrIeWJjy9cnj/0Tclmkba9p8wbkSEGdD1KvqaY4DjCDNk7cFpd4cdTJLKhfdWhLV/OnPhlEh/W46sIP72sd/23UqRYwBQuL237BxuTv7aUwjZotvEIBAbA8QJ9zaPHSP+aUaku4G6KPH5+b3bzsQJOTwDmkCoxAFWlVsoBkCvWUW5/S/7ZtwZvDe+TCl7v7aXz/MZP0wd1MFeDyv59Ojk7n1XP/JRAEisTr9uH21LJ/8TYwmBQP4PZDjJPKhTWITTudMZb18JNO/S+8yKdNRvFAlX6y/K6zt10sjYdzuvJivEfy3p2e3+zNmTIjs6GiIlSS8uH9l74kWh5lLLsG/GTuhp2abGkDl6NMGlmSH50SvnjQy2IWc/Pfv7liNEBm/DrqPHjh/iRQHgM4EKqFwDriEbAAUovnTuWiduMZ3h3quzHZPE671u36iHY88VKMuSLswIS7w/a+6ont5mFFHGm+sHNu9/XoYBQOJaDdi6rf+XZu416Deyb6f7T/NiKtDHy8MGxi+ZPbqblzlVUhBz99TeHVEZmn50jOjZv4O+VuI6Lto6/c7Q9Y/TK9CcI0O9YsYvmTOiq5cJpSrt1fVDB048yxJrOuQzd+3Y9qZM5J+ZwCAQCOR/GhyVSyUSmYpEowge79irDRDnOntRV0PdjEoQyL/+y4Q0ImNrEAkBAKFYjn2Iad8i/kjf7BnlVx2iizPsVJ5YhdXcoihL2NWTeIwdIlbfLq+9peTSgk4uvMbmHLqR79gf1vw0Y4A27Lf/ipv5EpQoSXgujAQAIBnajTmrLQcjSlK8P7Yo3MeC04QLFkJl8dzCpx17o3t9y4jv/NjfjjAFBO6KEymxVo2LtmRV5p9TgqyNuU0cVkLo+qY2vZbe4BMXa26R859v8ScsWm5j1z2RNSgwf78fMdBc48GP0AafFR+eGGKkuZM24nK2EsVwHEMV5X+tCOWxGtVMYpk4RG6O+mOINUejxdPNp9wWagfz2eG5NtoFxerzWUqd4cm7OKOTk6leUwHXaGxjq5BFF9NUGHwUIJD/FbQPvvjDnllBNQLZ6JuLiWJ1C8IOlyecm9ff35xLa0LsUlg8l+6z9z+rqCs9bpaXBVG4w/okZaMy8/+c08dQ86nZ5GXfdPWxpjUoj20ZMm7do6LPS3HtjBB/4scuRjoF2Kyq6QzGf7N7mKe5PquJjQQyy9DGNXLzK1FdLcL4w3OJSGH0zqvPJzZsN6Yue7tWK0X9+iz/WP0u+vHYwp5uPHoT0XgoLBOfEcvPZqDVHdFWUn5vdW9fex6zCSdKClPPNGDc/lcFylZPYBAIBAKpL6v5L85tmjRkxJjBIZbaDHMUq28uZamw/4xQFWc/X+FBGNLbjd0XI4Nf6f8G0KOhCVhOXQcMsMAAmRdgpLsfxvQK7TNiksQ8T63G/aZ2NKLXhWJBaByHTgN6khVsuw6uptQaGw5iOnTHKarFqn23kgpKKiVKFKEy2Xqm9h49R8+ZM7o9490ZihKPyZdiQqFErsJZdARQLTv1j6CjdH3zAEsqqAn9iiM0v4lbz3h33LPv9NPE3JKKKqlCDUgUGpNrYGrl0XnozJkT2puTdULWfGZLzcQjuFd/Vb4Y83TQpyCtdSoAOA4oDt8cfuR9YsvuM4+SiwWVIqkSBSQqg83VM7TxjZy8YN4gD3qt+ZRE4zl1Cw8zRbiOAS5GDXVMhl23AQNsMMDSa2/csA10m3adIyr0yuXMQAum9ngZicbrufLCSe7K7ZffFVdWSZUYicrk6utb+/f7btGCAa7sFH6M+loRIJFBcqa6TzsKoPBsvXuFh+Vh+h1cLVmIznBaD9v30LPblp0nH3wsEghEEs1oUuksjp6BtXePCXPnD/fjwfDnEMj/kE8DIcTZ7j37TZ2eZ5iJIgpO+PQO1oQ+1tidrFpO0D1H/nbCI2T/3jMPP+YVV4ikcjVOotKYHAMTa5eOw2fMGhdiTaoTu/o+3cP7O5SrUAsXTmO5wbDx7tCnD1qmMGw//NdNAzqvXn/qTU5hpVQFqCw9Uzu/8ImL54/w4H5eihMRvWk+QybPziolX3pdIJarMQw3LC9X4oCt6YtR+9mn7/se2Lb/2qu00spKzeQCyFQmR9/Q0LH94OmL5nS3ItXVQtGz9e4ZHuaA6Qe6WjZuN0IzcOkVFl5I5bp1cOdqpzZA8p649ZCl644DV99lF5ZXSeVKFKHQmBx9U1vXHqPmzBrbwahWfhIZKnjhP9+52nHHzkO3YnPKKjTzHQbIdCaba2Du2mHA9PnfdLFlgVZPYBAIBAKp2zPWTFosqrj4TdSFJO18Y2jTfvLv6/vbUoi5778xS5NpXBM9Zh4wMjJgw1N0/zPKV0uJFf8f9fCof7qnZq3Z6IPaD0HjT2oTvNR8IkiN+ZBZXKkic4ytnHx87TmgKe22qcpBbaTcmo9kRSnxKdmllVKcwtYzsXH38jBnN317K7vYphW1TqMVBQnvknNLxQpAYRtaOHi0c64xF1QnAmpuXFocaND8WNe8iQoz4t6nFlepKWxje09/DwtmE8PZYvV1lalKk94l5pRUyjEyy9DU3t3P1ZQO2jKcEAjkPyrdP/ec63ymKEmKT8ktEUgxCptrZOvq5W7FrXdNSxKtuVpEaW9jM0rEJK6Zo3egsxGp1WKn9ipVSeq7+NQiCU7VM3VsF+BmSK0neLGqnA/xaYXlYjWJxjG2cvH2s+V+bl6r/1bDWao6nBZecwpWXZYWn5RdJBArETrXxMbF28eO20SHdf4rzIr7mFFUIVaR6PpGls7ePjZ6JChxIRAI5G9SmfTXyYOHH+WqyVQ9x86j5n4Xbkn7O7nm/m3U4pL3d6JeFqFsK8/O3bq6GZHhdwoNDZAv022/VKVqzh7wL2toLVT3z7ak2dK/oNqWsvBChRcCgfyTYreJQttYXjNmE9CMJbdVou+riOPmq242EBGUuBAIBPJVxDGuViMUyn9NuH7W6A2BhgYIBAKBQCAQCAQCgfxfrtXh2V/I/y+AhgYIBAKBQCAQCAQCgUAgXw0SHAIIBAKBQCAQCAQCgUAgXwtoaIBAIBAIBAKBQCAQCATy1YCGBggEAoFAIBAIBAKBQCBfDWhogEAgEAgEAoFAIBAIBPLVgIYGCAQCgUAgEAgEAoFAIF8NaGiAQCAQCAQCgUAgEAgE8tWAhgYIBAKBQCAQCAQCgUAgXw1oaIBAIBAIBAKBQCAQCATy1YCGBggEAoFAIBAIBAKBQCBfDWhogEAgEAgEAoFAIBAIBPLVgIYGCAQCgUAgEAgEAoFAIF8NaGiAQCAQCAQCgUAgEAgE8tWAhgYIBAKBQCAQCAQCgUAgXw1oaIBAIBAIBAKBQCAQCATy1YCGBggEAoFAIBAIBAKBQCBfDWhogEAgEAgEAoFAIBAIBPLVgIYGCAQCgUAgEAgEAoFAIF+N/y8AAP//mMuBAoEQm74AAAAASUVORK5CYII="}}},{"cell_type":"code","source":"from zipfile import ZipFile\nfile_name = \"../input/quora-insincere-questions-classification/embeddings.zip\"\nwith ZipFile(file_name, 'r') as zip:\n     # printing all the contents of the zip file\n    zip.printdir()\n  \n    # extracting all the files\n    print('Extracting all the files now...')\n    zip.extractall()\n    print('Done!')","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:14:35.820091Z","iopub.execute_input":"2022-01-07T17:14:35.820358Z","iopub.status.idle":"2022-01-07T17:18:08.534844Z","shell.execute_reply.started":"2022-01-07T17:14:35.820325Z","shell.execute_reply":"2022-01-07T17:18:08.5341Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"glove_path = '../working/glove.840B.300d/glove.840B.300d.txt'\nparagram_path =  '../working/paragram_300_sl999/paragram_300_sl999.txt'\nwiki_news_path = '../working/wiki-news-300d-1M/wiki-news-300d-1M.vec'","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:18:08.536211Z","iopub.execute_input":"2022-01-07T17:18:08.536619Z","iopub.status.idle":"2022-01-07T17:18:08.540656Z","shell.execute_reply.started":"2022-01-07T17:18:08.536582Z","shell.execute_reply":"2022-01-07T17:18:08.539768Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"tokenize: tách câu văn thành các token(từ) và gắn cho nó 1 id bằng cách thống kê số đánh số thứ tự theo tần suất xuất hiện. Bằng cách vector hóa này ta có thể mã hóa được tất cả các từ vựng tuy nhiên nhược điểm sẽ là số chiều vector rất lớn ảnh hưởng tới xử lí và lưu trữ\npadding: tokenize chỉ giúp chúng ta mã hóa câu văn thành 1 matrix.Mà các câu văn có độ dài không đồng nhất, Để thuận tiện cho việc tính toán, huấn luyện mô hình người ta sẽ padding tất cả các chuỗi thành 100 từ ít hơn 100 thì họ thêm 0 còn nhiều hơn 100 thì đem cắt. Như vậy ta được vector 100 chiều ","metadata":{}},{"cell_type":"code","source":"train_df, val_df = train_test_split(train_df, test_size=0.1, random_state=2021)\nembed_size = 300 # how big is each word vector\nmax_features = 50000 # how many unique words to use (i.e num rows in embedding vector)\nmaxlen = 100 # max number of words in a question to use\n\ntrain_X = train_df[\"question_text\"].fillna(\"_na_\").values\nval_X = val_df[\"question_text\"].fillna(\"_na_\").values\ntest_X = test_df[\"question_text\"].fillna(\"_na_\").values\n\n## Tokenize the sentences\ntokenizer = Tokenizer(num_words=max_features)\ntokenizer.fit_on_texts(list(train_X))\ntrain_X = tokenizer.texts_to_sequences(train_X)\nval_X = tokenizer.texts_to_sequences(val_X)\ntest_X = tokenizer.texts_to_sequences(test_X)\n\n## Pad the sentences \ntrain_X = pad_sequences(train_X, maxlen=maxlen)\n\ntest_X = pad_sequences(test_X, maxlen=maxlen)\nval_X = pad_sequences(val_X, maxlen=maxlen)\ntest_X = pad_sequences(test_X, maxlen=maxlen)\n## Get the target values\ntrain_y = train_df['target'].values\nprint(\"Done\")","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:18:08.541839Z","iopub.execute_input":"2022-01-07T17:18:08.542231Z","iopub.status.idle":"2022-01-07T17:19:18.552411Z","shell.execute_reply.started":"2022-01-07T17:18:08.542198Z","shell.execute_reply":"2022-01-07T17:19:18.551565Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_y = train_df['target'].values\nval_y = val_df['target'].values","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:19:18.553813Z","iopub.execute_input":"2022-01-07T17:19:18.55431Z","iopub.status.idle":"2022-01-07T17:19:18.560333Z","shell.execute_reply.started":"2022-01-07T17:19:18.554272Z","shell.execute_reply":"2022-01-07T17:19:18.559468Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Vai trò của file embedding: mã hóa các word thành 1 vecto để model xử lí được. Thay vì ta thống kê chúng thì từ những file embedding này nó đã được gg  thực hiện sẵn và mã hóa các từ thành các vector số qua đó giúp chúng ta giảm thời gian train và cải thiện được hiệu suất","metadata":{}},{"cell_type":"code","source":"def load_glove(word_index):\n    def get_coefs(word,*arr): return word, np.asarray(arr, dtype='float32')[:300]\n    embeddings_index = dict(get_coefs(*o.split(\" \")) for o in open(glove_path))\n\n    all_embs = np.stack(embeddings_index.values())\n    emb_mean,emb_std = all_embs.mean(), all_embs.std()\n    embed_size = all_embs.shape[1]\n\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        if embedding_vector is not None: embedding_matrix[i] = embedding_vector\n            \n    return embedding_matrix \n\ndef load_fasttext(word_index):\n    def get_coefs(word,*arr): return word, np.asarray(arr, dtype='float32')\n    embeddings_index = dict(get_coefs(*o.split(\" \")) for o in open(wiki_news_path) if len(o)>100)\n\n    all_embs = np.stack(embeddings_index.values())\n    emb_mean,emb_std = all_embs.mean(), all_embs.std()\n    embed_size = all_embs.shape[1]\n\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        if embedding_vector is not None: embedding_matrix[i] = embedding_vector\n\n    return embedding_matrix\n\ndef load_para(word_index):\n    def get_coefs(word,*arr): return word, np.asarray(arr, dtype='float32')\n    embeddings_index = dict(get_coefs(*o.split(\" \")) for o in open(paragram_path, encoding=\"utf8\", errors='ignore') if len(o)>100)\n\n    all_embs = np.stack(embeddings_index.values())\n    emb_mean,emb_std = all_embs.mean(), all_embs.std()\n    embed_size = all_embs.shape[1]\n\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        if embedding_vector is not None: embedding_matrix[i] = embedding_vector\n    \n    return embedding_matrix","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:19:18.562063Z","iopub.execute_input":"2022-01-07T17:19:18.563615Z","iopub.status.idle":"2022-01-07T17:19:18.589237Z","shell.execute_reply.started":"2022-01-07T17:19:18.563577Z","shell.execute_reply":"2022-01-07T17:19:18.588304Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Ta sử dụng cả 3 bộ embedding để tăng độ phủ của các từ trong file embedding giúp hiệu quả hơn","metadata":{}},{"cell_type":"code","source":"glove_embedding = load_glove(tokenizer.word_index)\nfasttext_embedding = load_fasttext(tokenizer.word_index)\npara_embedding = load_para(tokenizer.word_index)\nembedding_matrix = np.mean([glove_embedding, fasttext_embedding, para_embedding], axis = 0)","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:19:18.593788Z","iopub.execute_input":"2022-01-07T17:19:18.59606Z","iopub.status.idle":"2022-01-07T17:28:33.09479Z","shell.execute_reply.started":"2022-01-07T17:19:18.596023Z","shell.execute_reply":"2022-01-07T17:28:33.093948Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Mô Hình","metadata":{}},{"cell_type":"markdown","source":"Đầu tiên xét về bài toán, đó là 1 bài toán nhị phân nên có rất nhiều cách giải quyết như hồi quy logistic hay SVM,LSTM,GRU. Ở đây em lựa chọn mô hình GRU vì nó có sẵn trong keras đồng thời nó phù hợp đối với những bài toán ngôn ngữ hay bài toán dạng chuỗi. Mạng GRU là 1 phiên bản hoàn thiện và tốt hơn của RNN\nMạng RNN là một loại mạng trong đó hidden state từ bước trước (mô tả ngữ cảnh của chuỗi đến thời điểm đó) làm đầu vào cho bước hiện tại. Nhưng mạng RNN có điểm yếu là không mô tả học được chuỗi quá dài do hiện tượng vanishing gradient.\nĐể giảm hiện tượng này thì GRU đã được trang bị thêm 2  cổng đó là update gate và reset gate. Hai cổng này sẽ quyết định thông tin nào sẽ được lưu lại truyền ở đầu ra hơn thế nữa nó sẽ được train để giữ thông tin từ trước đó và không xóa thông tin liên quan tới đầu ra\n\n![image.png](attachment:e1d2465c-e51c-4684-9404-3cf0595025ba.png)\n\nupdate gate: có nhiệm vụ xác định thông tin trước đó cần chuyển qua trạng thái tiếp theo\n$$z_t=\\sigma(W_z(x_t)+U_z(h_{t-1})$$ \n\nkết quả cho ra đi qua hàm sigmoid thu được kết quả từ 0-1. Update gate giúp mô hình ước lượng thông tin trong  hữu ích quá khứ. và bây giờ history: $z_t$ \n\nreset gate: thiết lập lại quyết định lượng thông tin quá khứ cần thiết cần bỏ qua.\n\nCông thức này giống như là công thức ở cổng update đã nêu trên. Sự khác biệt chỉ là ở trọng lượng và mức sử dụng của cổng này. \nNội dung nhớ hiện tại:\n$$h'_t=tanh(Wx_t+r_t*Uh_{t-1}$$\nQua đó sẽ giúp xác định chính xác thứ sẽ ảnh hưởng tới kết quả cuối cùng\n Bộ nhớ cuối cùng ở bước thời gian hiện tại:\n $$h_t=z_t*h_{t-1}+(1-z_t)*h'_t$$\n qua đó xác định được thông tin cần đưa vào mạng","metadata":{},"attachments":{"e1d2465c-e51c-4684-9404-3cf0595025ba.png":{"image/png":"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"}}},{"cell_type":"code","source":"inp = Input(shape=(maxlen,))\nx = Embedding(max_features, embed_size)(inp)\nx = Bidirectional(CuDNNGRU(64, return_sequences=True))(x)\nx = GlobalMaxPool1D()(x)\nx = Dense(16, activation=\"relu\")(x)\nx = Dropout(0.1)(x)\nx = Dense(1, activation=\"sigmoid\")(x)\nmodel = Model(inputs=inp, outputs=x)\nmodel.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\nprint(\"Done\")\nprint(model.summary())","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:28:33.096138Z","iopub.execute_input":"2022-01-07T17:28:33.096403Z","iopub.status.idle":"2022-01-07T17:28:35.422544Z","shell.execute_reply.started":"2022-01-07T17:28:33.096369Z","shell.execute_reply":"2022-01-07T17:28:35.421864Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#training\nmodel.fit(train_X,train_y,epochs=2,batch_size=512, validation_data=(val_X, val_y))\nprint(\"Done\")","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:28:35.423752Z","iopub.execute_input":"2022-01-07T17:28:35.424086Z","iopub.status.idle":"2022-01-07T17:31:58.69779Z","shell.execute_reply.started":"2022-01-07T17:28:35.424049Z","shell.execute_reply":"2022-01-07T17:31:58.695809Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Threshold","metadata":{}},{"cell_type":"markdown","source":"Bình thường ở các mô hình phân lớp nhị phân kết quả dự đoán luôn thuộc (0,1) threshold=0.5.\n\nNếu threshold < 0.5 thì phân lớp là negative, ngược lại thì là positive\n\nNhưng trong một số trường hợp, giá trị 0.5 này có thể chưa phải là tốt nhất. Trong bài toán này, mục đích của chúng ta tìm ra được càng nhiều câu không chân thành càng tốt, qua đó sẽ giúp giảm nội dung xấu trên quora vậy nên chọn threhold sao cho f1_score là cao nhất","metadata":{}},{"cell_type":"code","source":"pred_glove_val_y = model.predict([val_X], batch_size=1024, verbose=1)\nfor thresh in np.arange(0.1, 0.501, 0.01):\n    thresh = np.round(thresh, 2)\n    print(\"F1 score at threshold {0} is {1}\".format(thresh, metrics.f1_score(val_y, (pred_glove_val_y>thresh).astype(int))))","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:31:58.699207Z","iopub.execute_input":"2022-01-07T17:31:58.699472Z","iopub.status.idle":"2022-01-07T17:32:02.507199Z","shell.execute_reply.started":"2022-01-07T17:31:58.699436Z","shell.execute_reply":"2022-01-07T17:32:02.506402Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Ta lựa chọn threshold là 0.28\n","metadata":{}},{"cell_type":"code","source":"pred_test_y = model.predict([test_X], batch_size=1024, verbose=1)\npred_test_y = np.where(pred_test_y>0.28,1,0)                                \nout_df = pd.DataFrame({\"qid\":test_df[\"qid\"].values})\nout_df['prediction'] = pred_test_y\nout_df.to_csv(\"submission.csv\", index=False)","metadata":{"execution":{"iopub.status.busy":"2022-01-07T17:41:14.604268Z","iopub.execute_input":"2022-01-07T17:41:14.604861Z","iopub.status.idle":"2022-01-07T17:41:20.596919Z","shell.execute_reply.started":"2022-01-07T17:41:14.60482Z","shell.execute_reply":"2022-01-07T17:41:20.596194Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Kết quả: Nhìn chung mô hình đạt được độ chính xác f1_score: 65,5%\n\nĐể gia tăng hiệu quả mô hình em nghĩ cần tăng độ phủ của các file embedding lên toàn bộ file test và train qua đó sẽ giúp gia tăng độ hiệu quả của mô hình\n\n\n![32.png](attachment:6c13fd39-6483-442c-b6d8-5aeaaf06116b.png)","metadata":{},"attachments":{"6c13fd39-6483-442c-b6d8-5aeaaf06116b.png":{"image/png":"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"}}}]}