1209 lines (1208 with data), 368.4 kB
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Loading the data and required libraries"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import re\n",
"import datetime\n",
"import seaborn as sns\n",
"from matplotlib import pyplot as plt\n",
"# from google.colab import drive \n",
"\n",
"import string\n",
"import nltk\n",
"from nltk import word_tokenize\n",
"from nltk.stem.porter import PorterStemmer\n",
"from nltk.corpus import stopwords\n",
"\n",
"from sklearn.feature_extraction.text import CountVectorizer\n",
"from sklearn.model_selection import train_test_split\n",
"\n",
"from keras.models import Sequential, load_model\n",
"from keras.layers import LSTM, Dense, Dropout, Embedding, GRU, Conv1D, MaxPooling1D, SpatialDropout1D\n",
"from keras.optimizers import RMSprop, Adam\n",
"from keras.utils import to_categorical\n",
"from keras.callbacks import ModelCheckpoint\n",
"from keras.preprocessing.text import Tokenizer\n",
"from keras.utils import pad_sequences\n",
"from keras.utils.vis_utils import plot_model\n",
"\n",
"import tensorflow as tf"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import warnings\n",
"warnings.filterwarnings('ignore')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"DIR = \"E:/Coding/Summer 2023/data/\""
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"adm_notes = pd.read_csv(DIR + \"readmission.csv\", low_memory=False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Natural Language"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"def clean_text(texts):\n",
" texts = texts.fillna(' ')\n",
" texts = texts.str.replace('\\n',' ')\n",
" texts = texts.str.replace('\\r',' ')\n",
"\n",
" table = str.maketrans('', '', string.punctuation + '0123456789')\n",
" texts = [text.lower().translate(table) for text in texts]\n",
"\n",
" return texts"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"adm_notes['TEXT'] = clean_text(adm_notes['TEXT'])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"stop_words = stopwords.words('english')\n",
"stop_words = stop_words + ['patient', 'date', 'admission', 'discharge', 'lastname', 'firstname', 'sex']"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"porter = PorterStemmer()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"def tokenize_stem(text):\n",
" words = word_tokenize(text)\n",
" words = [word for word in words if word not in stop_words]\n",
" words = [porter.stem(word) for word in words]\n",
" return words"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"for i, text in enumerate(adm_notes['TEXT']):\n",
" adm_notes.loc[i, 'TEXT'] = (' ').join(tokenize_stem(adm_notes['TEXT'][i]))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Model\n",
"## Words, Train and Test"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Repartition data"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"df_train, df_test = train_test_split(adm_notes, test_size=0.2, random_state=42)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Subsample non-readmitted patients to match size of readmitted ones"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"rows_pos = df_train['READM_WITHIN_30'] == 1\n",
"df_train_pos = df_train.loc[rows_pos]\n",
"df_train_neg = df_train.loc[~rows_pos]\n",
"\n",
"df_train = pd.concat([df_train_pos, df_train_neg.sample(n = len(df_train_pos))], axis = 0)\n",
"df_train = df_train.sample(n = len(df_train)).reset_index(drop = True)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"rows_pos = df_test['READM_WITHIN_30'] == 1\n",
"df_test_pos = df_test.loc[rows_pos]\n",
"df_test_neg = df_test.loc[~rows_pos]\n",
"\n",
"df_test = pd.concat([df_test_pos, df_test_neg.sample(n = len(df_test_pos))], axis = 0)\n",
"df_test = df_test.sample(n = len(df_test)).reset_index(drop = True)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(4630, 10)\n",
"(1296, 10)\n"
]
}
],
"source": [
"print(df_train.shape)\n",
"print(df_test.shape)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Sparse Matrix with word count"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Recurrent Neural Network\n",
"## GRU"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"NUMBER_WORDS = 5000\n",
"\n",
"tokenizer = Tokenizer(num_words=NUMBER_WORDS)\n",
"tokenizer.fit_on_texts(df_train['TEXT'])\n",
"sequences_train = tokenizer.texts_to_sequences(df_train['TEXT'])\n",
"sequences_test = tokenizer.texts_to_sequences(df_test['TEXT'])\n",
"\n",
"X_train = pad_sequences(sequences_train, maxlen=NUMBER_WORDS)\n",
"X_test = pad_sequences(sequences_test, maxlen=NUMBER_WORDS)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"y_train = to_categorical(df_train['READM_WITHIN_30'])\n",
"y_test = to_categorical(df_test['READM_WITHIN_30'])"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"adam = Adam(learning_rate=0.0001)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Model: \"sequential\"\n",
"_________________________________________________________________\n",
" Layer (type) Output Shape Param # \n",
"=================================================================\n",
" embedding (Embedding) (None, 5000, 64) 320000 \n",
" \n",
" gru (GRU) (None, 64) 24960 \n",
" \n",
" dense (Dense) (None, 2) 130 \n",
" \n",
"=================================================================\n",
"Total params: 345,090\n",
"Trainable params: 345,090\n",
"Non-trainable params: 0\n",
"_________________________________________________________________\n"
]
}
],
"source": [
"model = Sequential()\n",
"model.add(Embedding(X_train.shape[1], 64, input_length=X_train.shape[1] ))\n",
"model.add(GRU(64, dropout=0.2))\n",
"model.add(Dense(2, activation='sigmoid'))\n",
"model.compile(loss='categorical_crossentropy', optimizer=adam, metrics=['accuracy'])\n",
"\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/10\n",
"58/58 [==============================] - 417s 7s/step - loss: 0.6929 - accuracy: 0.5119 - val_loss: 0.6919 - val_accuracy: 0.5637\n",
"Epoch 2/10\n",
"58/58 [==============================] - 408s 7s/step - loss: 0.6915 - accuracy: 0.5375 - val_loss: 0.6909 - val_accuracy: 0.5680\n",
"Epoch 3/10\n",
"58/58 [==============================] - 409s 7s/step - loss: 0.6906 - accuracy: 0.5486 - val_loss: 0.6895 - val_accuracy: 0.5648\n",
"Epoch 4/10\n",
"58/58 [==============================] - 408s 7s/step - loss: 0.6889 - accuracy: 0.5613 - val_loss: 0.6881 - val_accuracy: 0.5691\n",
"Epoch 5/10\n",
"58/58 [==============================] - 410s 7s/step - loss: 0.6871 - accuracy: 0.5756 - val_loss: 0.6866 - val_accuracy: 0.5616\n",
"Epoch 6/10\n",
"58/58 [==============================] - 409s 7s/step - loss: 0.6849 - accuracy: 0.5745 - val_loss: 0.6849 - val_accuracy: 0.5648\n",
"Epoch 7/10\n",
"58/58 [==============================] - 413s 7s/step - loss: 0.6830 - accuracy: 0.5856 - val_loss: 0.6836 - val_accuracy: 0.5670\n",
"Epoch 8/10\n",
"58/58 [==============================] - 409s 7s/step - loss: 0.6801 - accuracy: 0.5899 - val_loss: 0.6833 - val_accuracy: 0.5583\n",
"Epoch 9/10\n",
"58/58 [==============================] - 410s 7s/step - loss: 0.6780 - accuracy: 0.5934 - val_loss: 0.6828 - val_accuracy: 0.5637\n",
"Epoch 10/10\n",
"58/58 [==============================] - 415s 7s/step - loss: 0.6743 - accuracy: 0.5980 - val_loss: 0.6826 - val_accuracy: 0.5659\n"
]
}
],
"source": [
"history = model.fit(X_train, y_train, epochs = 10, batch_size = 64, validation_split=0.2)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['loss', 'accuracy']\n",
"21/21 [==============================] - 24s 1s/step - loss: 0.6812 - accuracy: 0.5687\n"
]
},
{
"data": {
"text/plain": [
"[0.6811752319335938, 0.5686728358268738]"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print(model.metrics_names)\n",
"model.evaluate(X_test, y_test, batch_size=64)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"21/21 [==============================] - 26s 1s/step\n",
" precision recall f1-score support\n",
"\n",
" 0 0.567 0.583 0.575 648\n",
" 1 0.571 0.554 0.562 648\n",
"\n",
" accuracy 0.569 1296\n",
" macro avg 0.569 0.569 0.569 1296\n",
"weighted avg 0.569 0.569 0.569 1296\n",
"\n",
"0.5686728395061728\n"
]
}
],
"source": [
"from sklearn.metrics import classification_report, roc_auc_score\n",
"\n",
"y_pred = model.predict(X_test, batch_size=64, verbose=1)\n",
"y_pred = np.argmax(y_pred, axis=1)\n",
"\n",
"y_test_raw = df_test['READM_WITHIN_30']\n",
"\n",
"print(classification_report(y_test_raw, y_pred, digits=3))\n",
"print(roc_auc_score(y_test_raw, y_pred))"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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",
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<Figure size 640x480 with 0 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set('talk', 'whitegrid', 'dark', font_scale=0.7,\n",
" rc={\"lines.linewidth\": 1, 'grid.linestyle': '--'})\n",
"\n",
"fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(9, 4))\n",
"\n",
"ax[0].plot(history.history['accuracy'])\n",
"ax[0].plot(history.history['val_accuracy'])\n",
"ax[0].set_title('Model accuracy')\n",
"ax[0].set_ylabel('Accuracy')\n",
"ax[0].set_xlabel('Epoch')\n",
"ax[0].legend(['Train', 'Test'], loc='upper left')\n",
"\n",
"ax[1].plot(history.history['loss'])\n",
"ax[1].plot(history.history['val_loss'])\n",
"ax[1].set_title('Model loss')\n",
"ax[1].set_ylabel('Loss')\n",
"ax[1].set_xlabel('Epoch')\n",
"ax[1].legend(['Train', 'Test'], loc='upper left')\n",
"\n",
"fig.tight_layout()\n",
"plt.show()\n",
"\n",
"plt.savefig('fig/gru.pgf')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Recurrent Neural Network\n",
"## LSTM"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"NUMBER_WORDS = 5000\n",
"\n",
"tokenizer = Tokenizer(num_words=NUMBER_WORDS)\n",
"tokenizer.fit_on_texts(df_train['TEXT'])\n",
"sequences_train = tokenizer.texts_to_sequences(df_train['TEXT'])\n",
"sequences_test = tokenizer.texts_to_sequences(df_test['TEXT'])\n",
"\n",
"X_train = pad_sequences(sequences_train, maxlen=NUMBER_WORDS)\n",
"X_test = pad_sequences(sequences_test, maxlen=NUMBER_WORDS)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"y_train = to_categorical(df_train['READM_WITHIN_30'])\n",
"y_test = to_categorical(df_test['READM_WITHIN_30'])"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"adam = Adam(learning_rate=0.00001)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Model: \"sequential_3\"\n",
"_________________________________________________________________\n",
" Layer (type) Output Shape Param # \n",
"=================================================================\n",
" embedding_3 (Embedding) (None, 5000, 32) 160000 \n",
" \n",
" lstm_1 (LSTM) (None, 32) 8320 \n",
" \n",
" dropout (Dropout) (None, 32) 0 \n",
" \n",
" dense_1 (Dense) (None, 2) 66 \n",
" \n",
"=================================================================\n",
"Total params: 168,386\n",
"Trainable params: 168,386\n",
"Non-trainable params: 0\n",
"_________________________________________________________________\n"
]
}
],
"source": [
"model = Sequential()\n",
"model.add(Embedding(X_train.shape[1], 32, input_length=X_train.shape[1] ))\n",
"model.add(LSTM(32, recurrent_dropout=0.2))\n",
"model.add(Dropout(0.2))\n",
"model.add(Dense(2, activation='sigmoid'))\n",
"model.compile(loss='categorical_crossentropy', optimizer=adam, metrics=['accuracy'])\n",
"\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/10\n",
"58/58 [==============================] - 461s 8s/step - loss: 0.6922 - accuracy: 0.5445 - val_loss: 0.6925 - val_accuracy: 0.5205\n",
"Epoch 2/10\n",
"58/58 [==============================] - 458s 8s/step - loss: 0.6921 - accuracy: 0.5486 - val_loss: 0.6925 - val_accuracy: 0.5205\n",
"Epoch 3/10\n",
"58/58 [==============================] - 458s 8s/step - loss: 0.6921 - accuracy: 0.5440 - val_loss: 0.6924 - val_accuracy: 0.5216\n",
"Epoch 4/10\n",
"58/58 [==============================] - 460s 8s/step - loss: 0.6920 - accuracy: 0.5427 - val_loss: 0.6924 - val_accuracy: 0.5335\n",
"Epoch 5/10\n",
"58/58 [==============================] - 459s 8s/step - loss: 0.6919 - accuracy: 0.5459 - val_loss: 0.6923 - val_accuracy: 0.5335\n",
"Epoch 6/10\n",
"58/58 [==============================] - 459s 8s/step - loss: 0.6919 - accuracy: 0.5478 - val_loss: 0.6923 - val_accuracy: 0.5313\n",
"Epoch 7/10\n",
"58/58 [==============================] - 461s 8s/step - loss: 0.6918 - accuracy: 0.5462 - val_loss: 0.6922 - val_accuracy: 0.5335\n",
"Epoch 8/10\n",
"58/58 [==============================] - 533s 9s/step - loss: 0.6918 - accuracy: 0.5462 - val_loss: 0.6922 - val_accuracy: 0.5313\n",
"Epoch 9/10\n",
"58/58 [==============================] - 714s 12s/step - loss: 0.6916 - accuracy: 0.5502 - val_loss: 0.6921 - val_accuracy: 0.5292\n",
"Epoch 10/10\n",
"58/58 [==============================] - 738s 13s/step - loss: 0.6915 - accuracy: 0.5570 - val_loss: 0.6921 - val_accuracy: 0.5281\n"
]
}
],
"source": [
"history = model.fit(X_train, y_train, epochs = 10, batch_size = 64, validation_split=0.2)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['loss', 'accuracy']\n",
"21/21 [==============================] - 21s 980ms/step - loss: 0.6917 - accuracy: 0.5517\n"
]
},
{
"data": {
"text/plain": [
"[0.6916937828063965, 0.5516975522041321]"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print(model.metrics_names)\n",
"model.evaluate(X_test, y_test, batch_size=64)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"21/21 [==============================] - 20s 911ms/step\n",
" precision recall f1-score support\n",
"\n",
" 0 0.561 0.478 0.516 648\n",
" 1 0.545 0.625 0.582 648\n",
"\n",
" accuracy 0.552 1296\n",
" macro avg 0.553 0.552 0.549 1296\n",
"weighted avg 0.553 0.552 0.549 1296\n",
"\n",
"0.5516975308641976\n"
]
}
],
"source": [
"from sklearn.metrics import classification_report, roc_auc_score\n",
"\n",
"y_pred = model.predict(X_test, batch_size=64, verbose=1)\n",
"y_pred = np.argmax(y_pred, axis=1)\n",
"\n",
"y_test_raw = df_test['READM_WITHIN_30']\n",
"\n",
"print(classification_report(y_test_raw, y_pred, digits=3))\n",
"print(roc_auc_score(y_test_raw, y_pred))"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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",
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<Figure size 640x480 with 0 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set('talk', 'whitegrid', 'dark', font_scale=0.7,\n",
" rc={\"lines.linewidth\": 1, 'grid.linestyle': '--'})\n",
"\n",
"fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(9, 4))\n",
"\n",
"ax[0].plot(history.history['accuracy'])\n",
"ax[0].plot(history.history['val_accuracy'])\n",
"ax[0].set_title('Model accuracy')\n",
"ax[0].set_ylabel('Accuracy')\n",
"ax[0].set_xlabel('Epoch')\n",
"ax[0].legend(['Train', 'Test'], loc='upper left')\n",
"\n",
"ax[1].plot(history.history['loss'])\n",
"ax[1].plot(history.history['val_loss'])\n",
"ax[1].set_title('Model loss')\n",
"ax[1].set_ylabel('Loss')\n",
"ax[1].set_xlabel('Epoch')\n",
"ax[1].legend(['Train', 'Test'], loc='upper left')\n",
"\n",
"fig.tight_layout()\n",
"plt.show()\n",
"\n",
"plt.savefig('fig/lstm.pgf')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Recurrent Neural Network\n",
"## GRU CNN"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"NUMBER_WORDS = 5000\n",
"\n",
"tokenizer = Tokenizer(num_words=NUMBER_WORDS)\n",
"tokenizer.fit_on_texts(df_train['TEXT'])\n",
"sequences_train = tokenizer.texts_to_sequences(df_train['TEXT'])\n",
"sequences_test = tokenizer.texts_to_sequences(df_test['TEXT'])\n",
"\n",
"X_train = pad_sequences(sequences_train, maxlen=NUMBER_WORDS)\n",
"X_test = pad_sequences(sequences_test, maxlen=NUMBER_WORDS)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"y_train = to_categorical(df_train['READM_WITHIN_30'])\n",
"y_test = to_categorical(df_test['READM_WITHIN_30'])"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"adam = Adam(learning_rate=0.00001)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Model: \"sequential\"\n",
"_________________________________________________________________\n",
" Layer (type) Output Shape Param # \n",
"=================================================================\n",
" embedding (Embedding) (None, 5000, 128) 640000 \n",
" \n",
" conv1d (Conv1D) (None, 4996, 128) 82048 \n",
" \n",
" max_pooling1d (MaxPooling1D (None, 1249, 128) 0 \n",
" ) \n",
" \n",
" gru (GRU) (None, 128) 99072 \n",
" \n",
" dense (Dense) (None, 2) 258 \n",
" \n",
"=================================================================\n",
"Total params: 821,378\n",
"Trainable params: 821,378\n",
"Non-trainable params: 0\n",
"_________________________________________________________________\n"
]
}
],
"source": [
"model = Sequential()\n",
"model.add(Embedding(X_train.shape[1], 128, input_length=X_train.shape[1] ))\n",
"model.add(Conv1D(128, 5, padding='valid', activation='relu', strides=1))\n",
"model.add(MaxPooling1D(pool_size=4))\n",
"model.add(GRU(128, dropout=0.2))\n",
"model.add(Dense(2, activation='sigmoid'))\n",
"model.compile(loss='categorical_crossentropy', optimizer=adam, metrics=['accuracy'])\n",
"\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/10\n",
"58/58 [==============================] - 290s 5s/step - loss: 0.6933 - accuracy: 0.5038 - val_loss: 0.6929 - val_accuracy: 0.5086\n",
"Epoch 2/10\n",
"58/58 [==============================] - 291s 5s/step - loss: 0.6926 - accuracy: 0.5165 - val_loss: 0.6922 - val_accuracy: 0.5378\n",
"Epoch 3/10\n",
"58/58 [==============================] - 284s 5s/step - loss: 0.6919 - accuracy: 0.5319 - val_loss: 0.6916 - val_accuracy: 0.5497\n",
"Epoch 4/10\n",
"58/58 [==============================] - 283s 5s/step - loss: 0.6912 - accuracy: 0.5470 - val_loss: 0.6910 - val_accuracy: 0.5551\n",
"Epoch 5/10\n",
"58/58 [==============================] - 282s 5s/step - loss: 0.6905 - accuracy: 0.5643 - val_loss: 0.6905 - val_accuracy: 0.5594\n",
"Epoch 6/10\n",
"58/58 [==============================] - 285s 5s/step - loss: 0.6898 - accuracy: 0.5697 - val_loss: 0.6900 - val_accuracy: 0.5648\n",
"Epoch 7/10\n",
"58/58 [==============================] - 285s 5s/step - loss: 0.6898 - accuracy: 0.5626 - val_loss: 0.6895 - val_accuracy: 0.5572\n",
"Epoch 8/10\n",
"58/58 [==============================] - 283s 5s/step - loss: 0.6888 - accuracy: 0.5734 - val_loss: 0.6890 - val_accuracy: 0.5605\n",
"Epoch 9/10\n",
"58/58 [==============================] - 283s 5s/step - loss: 0.6883 - accuracy: 0.5737 - val_loss: 0.6886 - val_accuracy: 0.5583\n",
"Epoch 10/10\n",
"58/58 [==============================] - 285s 5s/step - loss: 0.6878 - accuracy: 0.5805 - val_loss: 0.6881 - val_accuracy: 0.5670\n"
]
}
],
"source": [
"history = model.fit(X_train, y_train, epochs = 10, batch_size = 64, validation_split=0.2)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['loss', 'accuracy']\n",
"21/21 [==============================] - 37s 2s/step - loss: 0.6889 - accuracy: 0.5579\n"
]
},
{
"data": {
"text/plain": [
"[0.6889267563819885, 0.5578703880310059]"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print(model.metrics_names)\n",
"model.evaluate(X_test, y_test, batch_size=64)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"21/21 [==============================] - 35s 2s/step\n",
" precision recall f1-score support\n",
"\n",
" 0 0.575 0.446 0.502 648\n",
" 1 0.547 0.670 0.602 648\n",
"\n",
" accuracy 0.558 1296\n",
" macro avg 0.561 0.558 0.552 1296\n",
"weighted avg 0.561 0.558 0.552 1296\n",
"\n",
"0.5578703703703703\n"
]
}
],
"source": [
"from sklearn.metrics import classification_report, roc_auc_score\n",
"\n",
"y_pred = model.predict(X_test, batch_size=64, verbose=1)\n",
"y_pred = np.argmax(y_pred, axis=1)\n",
"\n",
"y_test_raw = df_test['READM_WITHIN_30']\n",
"\n",
"print(classification_report(y_test_raw, y_pred, digits=3))\n",
"print(roc_auc_score(y_test_raw, y_pred))"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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",
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<Figure size 640x480 with 0 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set('talk', 'whitegrid', 'dark', font_scale=0.7,\n",
" rc={\"lines.linewidth\": 1, 'grid.linestyle': '--'})\n",
"\n",
"fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(9, 4))\n",
"\n",
"ax[0].plot(history.history['accuracy'])\n",
"ax[0].plot(history.history['val_accuracy'])\n",
"ax[0].set_title('Model accuracy')\n",
"ax[0].set_ylabel('Accuracy')\n",
"ax[0].set_xlabel('Epoch')\n",
"ax[0].legend(['Train', 'Test'], loc='upper left')\n",
"\n",
"ax[1].plot(history.history['loss'])\n",
"ax[1].plot(history.history['val_loss'])\n",
"ax[1].set_title('Model loss')\n",
"ax[1].set_ylabel('Loss')\n",
"ax[1].set_xlabel('Epoch')\n",
"ax[1].legend(['Train', 'Test'], loc='upper left')\n",
"\n",
"fig.tight_layout()\n",
"plt.show()\n",
"\n",
"plt.savefig('fig/gru_cnn.pgf')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Recurrent Neural Network\n",
"## LSTM CNN"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"NUMBER_WORDS = 5000\n",
"\n",
"tokenizer = Tokenizer(num_words=NUMBER_WORDS)\n",
"tokenizer.fit_on_texts(df_train['TEXT'])\n",
"sequences_train = tokenizer.texts_to_sequences(df_train['TEXT'])\n",
"sequences_test = tokenizer.texts_to_sequences(df_test['TEXT'])\n",
"\n",
"X_train = pad_sequences(sequences_train, maxlen=NUMBER_WORDS)\n",
"X_test = pad_sequences(sequences_test, maxlen=NUMBER_WORDS)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"y_train = to_categorical(df_train['READM_WITHIN_30'])\n",
"y_test = to_categorical(df_test['READM_WITHIN_30'])"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
"adam = Adam(learning_rate=0.00001)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Model: \"sequential_1\"\n",
"_________________________________________________________________\n",
" Layer (type) Output Shape Param # \n",
"=================================================================\n",
" embedding_1 (Embedding) (None, 5000, 64) 320000 \n",
" \n",
" conv1d_1 (Conv1D) (None, 4996, 64) 20544 \n",
" \n",
" max_pooling1d_1 (MaxPooling (None, 1249, 64) 0 \n",
" 1D) \n",
" \n",
" lstm (LSTM) (None, 128) 98816 \n",
" \n",
" dense_1 (Dense) (None, 2) 258 \n",
" \n",
"=================================================================\n",
"Total params: 439,618\n",
"Trainable params: 439,618\n",
"Non-trainable params: 0\n",
"_________________________________________________________________\n"
]
}
],
"source": [
"model = Sequential()\n",
"model.add(Embedding(X_train.shape[1], 64, input_length=X_train.shape[1]))\n",
"model.add(Conv1D(64, 5, padding='valid', activation='relu', strides=1))\n",
"model.add(MaxPooling1D(pool_size=4))\n",
"model.add(LSTM(128, dropout=0.2, recurrent_dropout=0.2))\n",
"model.add(Dense(2, activation='sigmoid'))\n",
"model.compile(loss='categorical_crossentropy', optimizer=adam, metrics=['accuracy'])\n",
"\n",
"model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/10\n",
"58/58 [==============================] - 454s 8s/step - loss: 0.6932 - accuracy: 0.4911 - val_loss: 0.6930 - val_accuracy: 0.5205\n",
"Epoch 2/10\n",
"58/58 [==============================] - 410s 7s/step - loss: 0.6930 - accuracy: 0.5189 - val_loss: 0.6929 - val_accuracy: 0.5400\n",
"Epoch 3/10\n",
"58/58 [==============================] - 462s 8s/step - loss: 0.6927 - accuracy: 0.5400 - val_loss: 0.6928 - val_accuracy: 0.5389\n",
"Epoch 4/10\n",
"58/58 [==============================] - 520s 9s/step - loss: 0.6925 - accuracy: 0.5537 - val_loss: 0.6926 - val_accuracy: 0.5486\n",
"Epoch 5/10\n",
"58/58 [==============================] - 490s 8s/step - loss: 0.6925 - accuracy: 0.5335 - val_loss: 0.6925 - val_accuracy: 0.5486\n",
"Epoch 6/10\n",
"58/58 [==============================] - 567s 10s/step - loss: 0.6921 - accuracy: 0.5705 - val_loss: 0.6923 - val_accuracy: 0.5454\n",
"Epoch 7/10\n",
"58/58 [==============================] - 472s 8s/step - loss: 0.6920 - accuracy: 0.5613 - val_loss: 0.6922 - val_accuracy: 0.5562\n",
"Epoch 8/10\n",
"58/58 [==============================] - 516s 9s/step - loss: 0.6918 - accuracy: 0.5659 - val_loss: 0.6920 - val_accuracy: 0.5562\n",
"Epoch 9/10\n",
"58/58 [==============================] - 458s 8s/step - loss: 0.6916 - accuracy: 0.5759 - val_loss: 0.6918 - val_accuracy: 0.5551\n",
"Epoch 10/10\n",
"58/58 [==============================] - 404s 7s/step - loss: 0.6914 - accuracy: 0.5826 - val_loss: 0.6916 - val_accuracy: 0.5551\n"
]
}
],
"source": [
"history = model.fit(X_train, y_train, epochs = 10, batch_size = 64, validation_split=0.2)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['loss', 'accuracy']\n",
"21/21 [==============================] - 22s 1s/step - loss: 0.6916 - accuracy: 0.5633\n"
]
},
{
"data": {
"text/plain": [
"[0.6916040182113647, 0.5632715821266174]"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print(model.metrics_names)\n",
"model.evaluate(X_test, y_test, batch_size=64)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"21/21 [==============================] - 22s 1s/step\n",
" precision recall f1-score support\n",
"\n",
" 0 0.567 0.539 0.552 648\n",
" 1 0.560 0.588 0.574 648\n",
"\n",
" accuracy 0.563 1296\n",
" macro avg 0.563 0.563 0.563 1296\n",
"weighted avg 0.563 0.563 0.563 1296\n",
"\n",
"0.5632716049382716\n"
]
}
],
"source": [
"from sklearn.metrics import classification_report, roc_auc_score\n",
"\n",
"y_pred = model.predict(X_test, batch_size=64, verbose=1)\n",
"y_pred = np.argmax(y_pred, axis=1)\n",
"\n",
"y_test_raw = df_test['READM_WITHIN_30']\n",
"\n",
"print(classification_report(y_test_raw, y_pred, digits=3))\n",
"print(roc_auc_score(y_test_raw, y_pred))"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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",
"text/plain": [
"<Figure size 900x400 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<Figure size 640x480 with 0 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set('talk', 'whitegrid', 'dark', font_scale=0.7,\n",
" rc={\"lines.linewidth\": 1, 'grid.linestyle': '--'})\n",
"\n",
"fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(9, 4))\n",
"\n",
"ax[0].plot(history.history['accuracy'])\n",
"ax[0].plot(history.history['val_accuracy'])\n",
"ax[0].set_title('Model accuracy')\n",
"ax[0].set_ylabel('Accuracy')\n",
"ax[0].set_xlabel('Epoch')\n",
"ax[0].legend(['Train', 'Test'], loc='upper left')\n",
"\n",
"ax[1].plot(history.history['loss'])\n",
"ax[1].plot(history.history['val_loss'])\n",
"ax[1].set_title('Model loss')\n",
"ax[1].set_ylabel('Loss')\n",
"ax[1].set_xlabel('Epoch')\n",
"ax[1].legend(['Train', 'Test'], loc='upper left')\n",
"\n",
"fig.tight_layout()\n",
"plt.show()\n",
"\n",
"plt.savefig('fig/lstm_cnn.pgf')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.11"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}