L1 Regularization, L2 Regularization, Pruning, Support Vector Machine.
input_shape=(input_dim,)), # L1 regularization Dense(64, activation='relu', kernel_regularizer=l2(0.01)), # L2 regularization Dense(output_dim, activation='sigmoid') ]) model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy']) 4. Classification Models Controlling model