baseline_model

def get_features_only_model(n_features, n_classes):
    in_ = Input((n_features,))
    x = Dense(10, activation="relu", kernel_regularizer=l1(0.001))(in_)
    x = Dropout(0.5)(x)
    x = Dense(n_classes, activation="softmax")(x)

    model = Model(in_, x)

    model.compile(loss="sparse_categorical_crossentropy", metrics=['acc'], optimizer="adam")

    model.summary()

    return model