lvn_6

lvn_6.py

import pandas as pd
import numpy as np
from keras.models import Sequential
from keras.layers import Dense

data = pd.read_excel('assets/ENB2012_data.xlsx')

X = data.drop(axis=1, columns=['Y1', 'Y2'])
y = pd.concat([data['Y1'], data['Y2']], axis=1)

network = Sequential()
network.add(Dense(8, input_shape=(8,), activation='relu'))
network.add(Dense(6, activation='relu'))
network.add(Dense(6, activation='relu'))
network.add(Dense(4, activation='relu'))
network.add(Dense(2, activation='relu'))

network.compile('adam', loss='mse', metrics=['mse'])
network.fit(X, y, epochs=1000)