| import tensorflow as tf | |
| def create_model(input_shape=8): | |
| # neural network for binary classification | |
| model = tf.keras.Sequential([ | |
| tf.keras.layers.Input(shape=(input_shape,)), | |
| tf.keras.layers.Dense(64, activation='relu'), | |
| tf.keras.layers.Dense(32, activation='relu'), | |
| tf.keras.layers.Dense(1, activation='sigmoid') | |
| ]) | |
| model.compile( | |
| optimizer='adam', | |
| loss='binary_crossentropy', | |
| metrics=['accuracy'] | |
| ) | |
| return model |