lstm_twitter_classifier_unc.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"lstm_twitter_classifier_unc.ipynb","provenance":[],"collapsed_sections":[],"authorship_tag":"ABX9TyMDm4j9T82yxmyE66AG8zCh"},"kernelspec":{"name":"python3","display_name":"Python 3"},"accelerator":"GPU"},"cells":[{"cell_type":"code","metadata":{"id":"-0KxUxqRhA6c","colab_type":"code","outputId":"f40e1503-82d8-4bf0-ea61-32ee16a44ccc","executionInfo":{"status":"ok","timestamp":1591066706336,"user_tz":300,"elapsed":170379,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":122}},"source":["from google.colab import drive\n","drive.mount('/content/gdrive')"],"execution_count":0,"outputs":[{"output_type":"stream","text":["Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n","\n","Enter your authorization code:\n","··········\n","Mounted at /content/gdrive\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"g8XRWvQ4hLQn","colab_type":"code","outputId":"fb38fc71-5951-47aa-da29-9c4d640c4573","executionInfo":{"status":"ok","timestamp":1591066716064,"user_tz":300,"elapsed":180094,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":544}},"source":["from tensorflow.python.client import device_lib\n","print(device_lib.list_local_devices())"],"execution_count":0,"outputs":[{"output_type":"stream","text":["[name: \"/device:CPU:0\"\n","device_type: \"CPU\"\n","memory_limit: 268435456\n","locality {\n","}\n","incarnation: 9985042018943277700\n",", name: \"/device:XLA_CPU:0\"\n","device_type: \"XLA_CPU\"\n","memory_limit: 17179869184\n","locality {\n","}\n","incarnation: 12655565543386197559\n","physical_device_desc: \"device: XLA_CPU device\"\n",", name: \"/device:XLA_GPU:0\"\n","device_type: \"XLA_GPU\"\n","memory_limit: 17179869184\n","locality {\n","}\n","incarnation: 8422918663797743693\n","physical_device_desc: \"device: XLA_GPU device\"\n",", name: \"/device:GPU:0\"\n","device_type: \"GPU\"\n","memory_limit: 14648777152\n","locality {\n","  bus_id: 1\n","  links {\n","  }\n","}\n","incarnation: 17208784869352758789\n","physical_device_desc: \"device: 0, name: Tesla T4, pci bus id: 0000:00:04.0, compute capability: 7.5\"\n","]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"1Mam9lr7hN1G","colab_type":"code","outputId":"54bd5baa-eca2-4b7e-865c-f831664b8b81","executionInfo":{"status":"ok","timestamp":1591066717283,"user_tz":300,"elapsed":181303,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["import pandas as pd\n","import numpy as np\n","\n","import os.path\n","import pickle\n","from keras.preprocessing.text import Tokenizer, one_hot\n","from keras.preprocessing.sequence import pad_sequences\n","from keras.models import Sequential\n","\n","from keras.layers.core import Activation, Dropout, Dense\n","from keras.layers import Flatten, LSTM\n","from keras.layers import GlobalMaxPooling1D\n","from keras.models import Model\n","from keras.layers.normalization import BatchNormalization\n","\n","from sklearn.model_selection import train_test_split\n","from keras.utils.np_utils import to_categorical\n","from keras.callbacks import EarlyStopping\n","from keras.layers import Dropout, Input, Embedding\n","from keras.layers.merge import Concatenate\n","\n","import matplotlib.pyplot as plt\n","import nltk\n","import re\n","\n","from tqdm import tqdm\n","from sklearn.model_selection import train_test_split\n","from nltk.tokenize import word_tokenize\n","from nltk import pos_tag\n","from nltk.corpus import stopwords\n","from nltk.stem import WordNetLemmatizer\n","import nltk\n","\n","from numpy import array\n","from numpy import asarray\n","from numpy import zeros"],"execution_count":0,"outputs":[{"output_type":"stream","text":["Using TensorFlow backend.\n"],"name":"stderr"}]},{"cell_type":"code","metadata":{"id":"1obfAEAZhvEq","colab_type":"code","colab":{}},"source":["real = pd.read_csv('/content/gdrive/My Drive/twitter misinfo/2020_04_10000_real_tweets.csv', header = None)\n","fake = pd.read_csv('/content/gdrive/My Drive/twitter misinfo/2020_04_10000_fake_tweets_unconditional.csv', header = None)\n"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"rAnynOSUliMO","colab_type":"code","colab":{}},"source":["real.columns = ['tweet']"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"p49PZtpglRYr","colab_type":"code","colab":{}},"source":["real['index'] = real.index"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"016y4GbIz0JV","colab_type":"code","colab":{}},"source":["fake.columns = ['tweet']\n","fake['index'] = fake.index"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"ZTtODrJln2Hz","colab_type":"code","colab":{}},"source":["cols = real.columns.tolist()\n","cols = cols[-1:] + cols[:-1]"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"iPxiCb34yYkZ","colab_type":"code","colab":{}},"source":["real = real[cols]"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"VjZkUOsiycjq","colab_type":"code","colab":{}},"source":["cols = fake.columns.tolist()\n","cols = cols[-1:] + cols[:-1]\n","fake = fake[cols]"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"9KyVhjSXyxgu","colab_type":"code","outputId":"927c1145-7872-47c9-ef06-56e719c67411","executionInfo":{"status":"ok","timestamp":1591066718395,"user_tz":300,"elapsed":182344,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":204}},"source":["real['label'] = 1\n","fake['label'] = 0\n","real.head()"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>index</th>\n","      <th>tweet</th>\n","      <th>label</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>#Taiwan isn't a member of the #WHO.  Taiwan tr...</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>From the DJs to the CJs.. Look whose in the PJ...</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>The @ClinicalBioinfo led by @xdopazo releases ...</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>IMF expects #Greece to be the worst hit econom...</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>More on #COVID19 - China witnessed a slight in...</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   index                                              tweet  label\n","0      0  #Taiwan isn't a member of the #WHO.  Taiwan tr...      1\n","1      1  From the DJs to the CJs.. Look whose in the PJ...      1\n","2      2  The @ClinicalBioinfo led by @xdopazo releases ...      1\n","3      3  IMF expects #Greece to be the worst hit econom...      1\n","4      4  More on #COVID19 - China witnessed a slight in...      1"]},"metadata":{"tags":[]},"execution_count":11}]},{"cell_type":"code","metadata":{"id":"JKEts42ozfp0","colab_type":"code","outputId":"1e7fe5bd-78ae-42e3-f527-7093b0294ae5","executionInfo":{"status":"ok","timestamp":1591066718396,"user_tz":300,"elapsed":182334,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":204}},"source":["fake.head()"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>index</th>\n","      <th>tweet</th>\n","      <th>label</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>@chrislhayes I think it's important to note th...</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>The problem is, it's the Chinese that are bein...</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>Do you know of any people who are looking for ...</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>Just as the COVID-19 pandemic has shown that t...</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>Covid-19's impact on the economy: The RBC Stat...</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   index                                              tweet  label\n","0      0  @chrislhayes I think it's important to note th...      0\n","1      1  The problem is, it's the Chinese that are bein...      0\n","2      2  Do you know of any people who are looking for ...      0\n","3      3  Just as the COVID-19 pandemic has shown that t...      0\n","4      4  Covid-19's impact on the economy: The RBC Stat...      0"]},"metadata":{"tags":[]},"execution_count":12}]},{"cell_type":"code","metadata":{"id":"v3POeDqX0X5j","colab_type":"code","outputId":"54103872-36f5-4132-b186-cea5dbd62f99","executionInfo":{"status":"ok","timestamp":1591066718396,"user_tz":300,"elapsed":182324,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":204}},"source":["combined = pd.concat([fake, real])\n","features = combined['tweet']\n","labels = combined['label']\n","combined = combined.sample(frac = 1).reset_index(drop = True)\n","combined['index'] = combined.index\n","combined.tail()"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>index</th>\n","      <th>tweet</th>\n","      <th>label</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>19992</th>\n","      <td>19992</td>\n","      <td>*Hears about a deadly virus going around* *Fin...</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>19993</th>\n","      <td>19993</td>\n","      <td>The mother of Manchester City manager Pep Guar...</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>19994</th>\n","      <td>19994</td>\n","      <td>#COVID19 Updates 👇</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>19995</th>\n","      <td>19995</td>\n","      <td>Each penny counts. Contribute whatever you can...</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>19996</th>\n","      <td>19996</td>\n","      <td>Great work @DJLuzo.  We are more than ever pro...</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["       index                                              tweet  label\n","19992  19992  *Hears about a deadly virus going around* *Fin...      1\n","19993  19993  The mother of Manchester City manager Pep Guar...      1\n","19994  19994                                 #COVID19 Updates 👇      0\n","19995  19995  Each penny counts. Contribute whatever you can...      1\n","19996  19996  Great work @DJLuzo.  We are more than ever pro...      0"]},"metadata":{"tags":[]},"execution_count":13}]},{"cell_type":"code","metadata":{"id":"5aWZxqhuFTU-","colab_type":"code","outputId":"3f64de17-5f4d-45a8-e0fe-ce9b13bb182a","executionInfo":{"status":"ok","timestamp":1591066718397,"user_tz":300,"elapsed":182315,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":68}},"source":["nltk.download('stopwords')"],"execution_count":0,"outputs":[{"output_type":"stream","text":["[nltk_data] Downloading package stopwords to /root/nltk_data...\n","[nltk_data]   Unzipping corpora/stopwords.zip.\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["True"]},"metadata":{"tags":[]},"execution_count":14}]},{"cell_type":"code","metadata":{"id":"kUMRhaIy9BZ4","colab_type":"code","outputId":"64104acb-e721-4576-f8b9-f62f1d8baf93","executionInfo":{"status":"ok","timestamp":1591066718724,"user_tz":300,"elapsed":182632,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":204}},"source":["# combined['tweet'] = [entry.lower() for entry in combined['tweet']]\n","combined['tweet_lower'] = combined['tweet'].astype(str).str.replace('[^a-zA-Z]',' ').str.lower()\n","combined.head()"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>index</th>\n","      <th>tweet</th>\n","      <th>label</th>\n","      <th>tweet_lower</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>The reported #COVID19 cases in the #Indian cap...</td>\n","      <td>0</td>\n","      <td>the reported  covid   cases in the  indian cap...</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>#COVID19  \"When you are ready, let's be ready....</td>\n","      <td>0</td>\n","      <td>covid     when you are ready  let s be ready ...</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>#AskATeeSood  #COVID19 #WednesdayThoughts</td>\n","      <td>0</td>\n","      <td>askateesood   covid    wednesdaythoughts</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>Corporate greed blocked manufacture of inexpen...</td>\n","      <td>1</td>\n","      <td>corporate greed blocked manufacture of inexpen...</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>Retweet if you are able to get the photos that...</td>\n","      <td>0</td>\n","      <td>retweet if you are able to get the photos that...</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   index  ...                                        tweet_lower\n","0      0  ...  the reported  covid   cases in the  indian cap...\n","1      1  ...   covid     when you are ready  let s be ready ...\n","2      2  ...           askateesood   covid    wednesdaythoughts\n","3      3  ...  corporate greed blocked manufacture of inexpen...\n","4      4  ...  retweet if you are able to get the photos that...\n","\n","[5 rows x 4 columns]"]},"metadata":{"tags":[]},"execution_count":15}]},{"cell_type":"code","metadata":{"id":"VmxeumtG9W3-","colab_type":"code","colab":{}},"source":["stop_re = '\\\\b'+'\\\\b|\\\\b'.join(nltk.corpus.stopwords.words('english'))+'\\\\b'\n","combined['tweet_stop'] = combined['tweet_lower'].astype(str).str.replace(stop_re, '')"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"afwzOYlACQ99","colab_type":"code","outputId":"721ed9e7-4fc1-4510-a1de-903d182848e2","executionInfo":{"status":"ok","timestamp":1591066718956,"user_tz":300,"elapsed":182846,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":204}},"source":["combined['tweet_stop'].head(10)"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0     reported  covid   cases    indian capital   t...\n","1     covid        ready  let   ready      coronavi...\n","2             askateesood   covid    wednesdaythoughts\n","3    corporate greed blocked manufacture  inexpensi...\n","4            retweet    able  get  photos  look like  \n","5     people   realize        twitter  amp  faceboo...\n","6     covid       new cases confirmed      patients...\n","7    today   covid   day  tablighijamaat  tablighii...\n","8        covid doctors   per request     original e...\n","9       told     fair   pms must   place  corona   ...\n","Name: tweet_stop, dtype: object"]},"metadata":{"tags":[]},"execution_count":17}]},{"cell_type":"code","metadata":{"id":"lrXAyyiZCxXd","colab_type":"code","colab":{}},"source":["combined['tweet_final'] = combined['tweet_stop'].astype(str).str.split()"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"fPpwIHDsDLZK","colab_type":"code","colab":{}},"source":["x = []\n","sentences = list(combined[\"tweet_final\"])\n","for line in combined['tweet_final']:\n","    x.append(line)\n","\n","y = labels"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"556jEvDsDOMM","colab_type":"code","outputId":"599f5855-bda9-4b44-9648-58cc1f043e0a","executionInfo":{"status":"ok","timestamp":1591066719758,"user_tz":300,"elapsed":183617,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":221}},"source":["y"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0       0\n","1       0\n","2       0\n","3       0\n","4       0\n","       ..\n","9995    1\n","9996    1\n","9997    1\n","9998    1\n","9999    1\n","Name: label, Length: 19997, dtype: int64"]},"metadata":{"tags":[]},"execution_count":20}]},{"cell_type":"code","metadata":{"id":"eqe-FO6H9ne9","colab_type":"code","colab":{}},"source":["# final_tweet_text = []\n","# for entry in tqdm(combined['tweet_lower']):\n","#         # Declaring Empty List to store the words that follow the rules for this step\n","#         Final_words = []\n","#         # Initializing WordNetLemmatizer()\n","#         word_Lemmatized = WordNetLemmatizer()\n","#         # pos_tag function below will provide the 'tag' i.e if the word is Noun(N) or Verb(V) or something else.\n","#         for word, tag in pos_tag(entry):\n","#             # Below condition is to check for Stop words and consider only alphabets\n","#             if word not in stopwords.words('english') and word.isalpha():\n","#                 word_Final = word_Lemmatized.lemmatize(word,tag_map[tag[0]])\n","#                 Final_words.append(word_Final)\n","#         final_comment_text.append(Final_words)\n","#     # The final processed set of words for each iteration will be stored in 'text_final'\n","#     combined['tweet_final'] = final_comment_text\n","#     combined.to_pickle(\"final_pickle_unc.pkl\")\n","# combined.head()"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"QvTXLgSY0zKQ","colab_type":"code","colab":{}},"source":["x_train,x_test,y_train,y_test = train_test_split(x, y, test_size = 0.33, random_state = 42)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"dWtzyBL3Dimw","colab_type":"code","colab":{}},"source":["tokenizer = Tokenizer(num_words=5000)\n","tokenizer.fit_on_texts(x_train)\n","\n","x_train = tokenizer.texts_to_sequences(x_train)\n","x_test = tokenizer.texts_to_sequences(x_test)\n","\n","vocab_size = len(tokenizer.word_index) + 1\n","\n","maxlen = 200\n","\n","x_train = pad_sequences(x_train, padding='post', maxlen=maxlen)\n","x_test = pad_sequences(x_test, padding='post', maxlen=maxlen)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"Z3NNVE5j8RbN","colab_type":"code","colab":{}},"source":["embeddings_dictionary = dict()\n","\n","glove_file = open('/content/gdrive/My Drive/twitter misinfo/glove.6B.100d.txt', encoding=\"utf8\")\n","\n","for line in glove_file:\n","    records = line.split()\n","    word = records[0]\n","    vector_dimensions = asarray(records[1:], dtype='float32')\n","    embeddings_dictionary[word] = vector_dimensions\n","glove_file.close()\n","\n","embedding_matrix = zeros((vocab_size, 100))\n","for word, index in tokenizer.word_index.items():\n","    embedding_vector = embeddings_dictionary.get(word)\n","    if embedding_vector is not None:\n","        embedding_matrix[index] = embedding_vector"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"6D6gRBPyD95N","colab_type":"code","colab":{}},"source":["# deep_inputs = Input(shape=(maxlen,))\n","# embedding_layer = Embedding(vocab_size, 100, weights=[embedding_matrix], trainable=False)(deep_inputs)\n","# LSTM_Layer_1 = LSTM(128)(embedding_layer)\n","# dense_layer_1 = Dense(1, activation='sigmoid')(LSTM_Layer_1)\n","# model = Model(inputs=deep_inputs, outputs=dense_layer_1)\n","\n","# model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['acc'])"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"juY0UM9yJd_o","colab_type":"code","colab":{}},"source":["# embed_dim = 50\n","# lstm_out = 64\n","# batch_size = 32\n","# max_words = 5000\n","# model = Sequential()\n","# model.add(Embedding(max_words, embed_dim, input_length = maxlen))\n","# model.add(LSTM(lstm_out))\n","# model.add(Dense(256))\n","# model.add(Activation('relu'))\n","# model.add(Dropout(0.5))\n","# model.add(Dense(1, name='out_layer'))\n","# model.add(Activation('sigmoid'))\n","# model.compile(loss = 'binary_crossentropy', optimizer='adam', metrics = ['accuracy'])\n","# print(model.summary())"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"Nhl5z9FBNKUr","colab_type":"code","outputId":"5c94fe8d-7920-474f-8344-e1aec4628006","executionInfo":{"status":"ok","timestamp":1591066733411,"user_tz":300,"elapsed":197196,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":442}},"source":["embed_dim = 100\n","lstm_out = 64\n","batch_size = 128\n","max_words = 5000\n","model = Sequential()\n","model.add(Embedding(max_words, embed_dim, input_length = maxlen))\n","model.add(LSTM(lstm_out))\n","model.add(Dense(256))\n","model.add(Activation('sigmoid'))\n","model.add(BatchNormalization())\n","model.add(Dropout(0.5))\n","model.add(Dense(1, name='out_layer'))\n","model.add(Activation('sigmoid'))\n","model.compile(loss = 'binary_crossentropy', optimizer='adam', metrics = ['acc'])\n","print(model.summary())"],"execution_count":0,"outputs":[{"output_type":"stream","text":["Model: \"sequential_1\"\n","_________________________________________________________________\n","Layer (type)                 Output Shape              Param #   \n","=================================================================\n","embedding_1 (Embedding)      (None, 200, 100)          500000    \n","_________________________________________________________________\n","lstm_1 (LSTM)                (None, 64)                42240     \n","_________________________________________________________________\n","dense_1 (Dense)              (None, 256)               16640     \n","_________________________________________________________________\n","activation_1 (Activation)    (None, 256)               0         \n","_________________________________________________________________\n","batch_normalization_1 (Batch (None, 256)               1024      \n","_________________________________________________________________\n","dropout_1 (Dropout)          (None, 256)               0         \n","_________________________________________________________________\n","out_layer (Dense)            (None, 1)                 257       \n","_________________________________________________________________\n","activation_2 (Activation)    (None, 1)                 0         \n","=================================================================\n","Total params: 560,161\n","Trainable params: 559,649\n","Non-trainable params: 512\n","_________________________________________________________________\n","None\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"r3bgYeSBEKIf","colab_type":"code","outputId":"611e6925-a01f-4643-c460-737f54ba4cbd","executionInfo":{"status":"ok","timestamp":1591067245754,"user_tz":300,"elapsed":637,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":258}},"source":["history = model.fit(x_train, y_train, batch_size=batch_size, epochs=5, validation_split=0.2)"],"execution_count":0,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/indexed_slices.py:434: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory.\n","  \"Converting sparse IndexedSlices to a dense Tensor of unknown shape. \"\n"],"name":"stderr"},{"output_type":"stream","text":["Train on 10717 samples, validate on 2680 samples\n","Epoch 1/5\n","10717/10717 [==============================] - 32s 3ms/step - loss: 0.6935 - acc: 0.4978 - val_loss: 0.7287 - val_acc: 0.5067\n","Epoch 2/5\n","10717/10717 [==============================] - 29s 3ms/step - loss: 0.6933 - acc: 0.4980 - val_loss: 0.7030 - val_acc: 0.5067\n","Epoch 3/5\n","10717/10717 [==============================] - 29s 3ms/step - loss: 0.6933 - acc: 0.4987 - val_loss: 0.6955 - val_acc: 0.5067\n","Epoch 4/5\n","10717/10717 [==============================] - 29s 3ms/step - loss: 0.6934 - acc: 0.5003 - val_loss: 0.6934 - val_acc: 0.5067\n","Epoch 5/5\n","10717/10717 [==============================] - 29s 3ms/step - loss: 0.6936 - acc: 0.4964 - val_loss: 0.6931 - val_acc: 0.5067\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"yhXJO9mqEO8E","colab_type":"code","colab":{}},"source":["# pickle.dump(history, open('lstm_model_unc.sav', 'wb'))"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"48Tjm9djEepb","colab_type":"code","outputId":"205df4c4-f6d7-4721-a67d-f34b5a8e282b","executionInfo":{"status":"ok","timestamp":1591067245756,"user_tz":300,"elapsed":60,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":85}},"source":["score = model.evaluate(x_test, y_test, verbose=1)\n","\n","print(\"Test Score:\", score[0])\n","print(\"Test Accuracy:\", score[1])\n","print(score)"],"execution_count":0,"outputs":[{"output_type":"stream","text":["6600/6600 [==============================] - 6s 936us/step\n","Test Score: 0.6933950088963364\n","Test Accuracy: 0.49742424488067627\n","[0.6933950088963364, 0.49742424488067627]\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"a6wPFL7lEhIk","colab_type":"code","outputId":"c2e21108-c3a9-41b0-ebc3-98728dcaa837","executionInfo":{"status":"ok","timestamp":1591067245756,"user_tz":300,"elapsed":41,"user":{"displayName":"Mukund Srinath Heragu","photoUrl":"","userId":"03076730854199538823"}},"colab":{"base_uri":"https://localhost:8080/","height":573}},"source":["plt.plot(history.history['acc'])\n","plt.plot(history.history['val_acc'])\n","\n","plt.title('model accuracy')\n","plt.ylabel('accuracy')\n","plt.xlabel('epoch')\n","plt.legend(['train','test'], loc='upper left')\n","plt.show()\n","\n","plt.plot(history.history['loss'])\n","plt.plot(history.history['val_loss'])\n","\n","plt.title('model loss')\n","plt.ylabel('loss')\n","plt.xlabel('epoch')\n","plt.legend(['train','test'], loc='upper left')\n","plt.show()"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"mqPr1ZJNJUX6","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]}]}