DenseNetInterface

class ketos.neural_networks.densenet.DenseNetInterface(dense_blocks=[6, 12, 24, 16], growth_rate=32, compression_factor=0.5, n_classes=2, dropout_rate=0.2, optimizer=Adam ketos recipe, loss_function=CategoricalCrossentropy ketos recipe, metrics=[BinaryAccuracy ketos recipe, Precision ketos recipe, Recall ketos recipe])[source]

Methods

Attributes

checkpoint_dir

early_stopping_monitor

Sets an early stopping monitor.

log_dir

test_generator

train_generator

val_generator

valid_losses

valid_metrics

valid_optimizers