create-keras-ann.md

Create keras ANN

import keras
from keras.models import Sequential
from keras.layers import Dense

# Initialization
classifier = Sequential()

# Add first layer
classifier.add(Dense(units = 6, activation = 'relu', kernel_initializer = 'uniform', input_dim = 11))

# Add hidden layer
classifier.add(Dense(units = 6, activation = 'relu', kernel_initializer = 'uniform'))

# Add output layer
classifier.add(Dense(units = 1, activation = 'sigmoid', kernel_initializer = 'uniform'))

# Compile model
classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])

# training model
classifier.fit(X_train, y_train, batch_size = 10, epochs = 100)

# Predicting the Test set results
y_pred = classifier.predict(X_test)
y_pred = (y_pred > 0.5)

# Making the Confusion Matrix
from sklearn.metrics import confusion_matrix
confusion_matrix(y_test, y_pred)