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Runtime error
| import numpy as np | |
| import pandas as pd | |
| from tensorflow import keras | |
| from keras import Sequential | |
| from keras.layers import Dense,Dropout,LSTM | |
| class model_builder: | |
| def __init__(self): | |
| self.model = None | |
| def preprocess_data(self,dataset,time_step): | |
| dataX, dataY = [], [] | |
| for i in range(len(dataset)-time_step-1): | |
| a = dataset[i:(i+time_step), 0] | |
| dataX.append(a) | |
| dataY.append(dataset[i + time_step, 0]) | |
| return np.array(dataX), np.array(dataY) | |
| def create_model(self,X_train): | |
| model = Sequential() | |
| model.add(LSTM(150,return_sequences=True,input_shape=(X_train.shape[1],X_train.shape[2]))) | |
| model.add(Dropout(0.2)) | |
| model.add(LSTM(150,return_sequences=True)) | |
| model.add(Dropout(0.2)) | |
| model.add(LSTM(150)) | |
| model.add(Dropout(0.2)) | |
| model.add(Dense(1)) | |
| model.compile(loss='mean_squared_error' , metrics = ['mse', 'mae'],optimizer='adam') | |
| return model | |
| def fit(self,X_train,y_train): | |
| model = self.create_model(X_train) | |
| model.fit(X_train,y_train,epochs=300,batch_size=64,verbose=1) | |
| self.model = model | |
| return model | |