I create my first artificial perceptron multilayer neural network using Keras.
This is my input:

This is my code that I used to create my initial model, which basically follows the Keras code example:
model = Sequential()
model.add(Dense(64, input_dim=14, init='uniform'))
model.add(Activation('tanh'))
model.add(Dropout(0.5))
model.add(Dense(64, init='uniform'))
model.add(Activation('tanh'))
model.add(Dropout(0.5))
model.add(Dense(2, init='uniform'))
model.add(Activation('softmax'))
sgd = SGD(lr=0.1, decay=1e-6, momentum=0.9, nesterov=True)
model.compile(loss='mean_squared_error', optimizer=sgd)
model.fit(X_train, y_train, nb_epoch=20, batch_size=16)
Output:
Epoch 1/20
1213/1213 [
Epoch 2/20
1213/1213 [
Epoch 3/20
1213/1213 [
Epoch 4/20
1213/1213 [
Epoch 5/20
1213/1213 [
Epoch 6/20
1213/1213 [
Epoch 7/20
1213/1213 [
Epoch 8/20
1213/1213 [
Epoch 9/20
1213/1213 [
Epoch 10/20
1213/1213 [
Epoch 11/20
1213/1213 [
Epoch 12/20
1213/1213 [
Epoch 13/20
1213/1213 [
Epoch 14/20
1213/1213 [
Epoch 15/20
1213/1213 [
Epoch 16/20
1213/1213 [
Epoch 17/20
1213/1213 [
Epoch 18/20
1213/1213 [
Epoch 19/20
1213/1213 [
Epoch 20/20
1213/1213 [
How do I prepare and configure this model and get my code to output my best predictive model? I'm new to neural networks, and I'm just completely confused about what is the next step after creating a model. I know that I want to optimize it, but I'm not sure what functions need to be configured or if I have to do it manually or how to write code for this.