text_plain_output_1.png
from keras.layers import Dense

from keras.models import Sequential

model_1 = Sequential()
model_1.add(Dense(25, input_dim=20, activation='relu'))
model_1.add(Dense(25, activation='relu'))
model_1.add(Dense(4, activation='softmax'))
model_1.summary()

model_1.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
hist_1 = model_1.fit(X_train, y_train, epochs=20, batch_size=25, validation_data=(X_val, y_val))

score = model_1.evaluate(X_val, y_val, verbose=0)
print('Test loss:', score[0])
print('Test accuracy:', score[1])