Simple Feed-Forward Fully Connected Neural Network

neuralnet.py

import tensorflow as tf
from tensorflow import keras

nn = keras.Sequential(name='CovidClassification')
nn.add(keras.Input(shape=(X_train.shape[1],)))
nn.add(keras.layers.Dense(
    units=4,
    activation='leaky_relu',
    kernel_regularizer=keras.regularizers.L2(),
    bias_regularizer=keras.regularizers.L2(),
    name='hidden_layer'
))
nn.add(keras.layers.Dense(units=2, activation='softmax', name='output_layer'))
nn.summary()

nn.compile(
    optimizer=keras.optimizers.Adam(),
    loss=keras.losses.CategoricalCrossentropy(),
    metrics=[
        keras.metrics.AUC(name='auc'),
        keras.metrics.Precision(),
        keras.metrics.Recall()
    ]
)

y_train_encoded = keras.utils.to_categorical(y_train, num_classes=2)
y_val_encoded = keras.utils.to_categorical(y_val, num_classes=2)

training = nn.fit(
    X_train, y_train_encoded,
    batch_size=32,
    epochs=2,
    verbose=2,
    callbacks=[
        keras.callbacks.EarlyStopping(
            monitor='val_auc',
            patience=5,
            mode='max',
            restore_best_weights=True
        )
    ],
    validation_data=(X_val, y_val_encoded)
)