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`