Reference

All functions

KerasArchitecture

Keras Neural Network architecture base class

LearnerClassifKeras

Keras Neural Network with custom architecture (Classification)

LearnerClassifKerasCNN

Keras CNN Architectures for Classification

LearnerClassifKerasDeepWide

Keras Feed Forward Neural Network for Classification with a deep and wide part

LearnerClassifKerasFF

Keras Feed Forward Neural Network for Classification

LearnerClassifShapedMLP

Keras Feed Forward Neural Network for Classification: Shaped MLP

LearnerClassifShapedMLP2

Keras Feed Forward Neural Network for Classification: Shaped MLP 2 Currently does not allow Shake-Shake, Shake-Drop or Mixup training as well as SVD on sparse matrices.

LearnerClassifTabNet

Keras TabNet Neural Network for Classification

LearnerRegrKeras

Keras Neural Network with custom architecture (Regression)

LearnerRegrKerasDeepWide

Keras Feed Forward Neural Network for Regression with a deep and wide part

LearnerRegrKerasFF

Keras Feed Forward Neural Network for Regression

LearnerRegrShapedMLP

Keras Feed Forward Neural Network for Regression: Shaped MLP

LearnerRegrShapedMLP2

Keras Feed Forward Neural Network for Regression: Shaped MLP 2 Currently does not allow Shake-Shake, Shake-Drop or Mixup training as well as SVD on sparse matrices.

LearnerRegrTabNet

Keras TabNet Neural Network for Regression

cb_es() cb_lr_scheduler_cosine_anneal() cb_lr_scheduler_exponential_decay() cb_tensorboard() cb_lr_log()

cb_es: Early stopping callback

combine_generators()

Make a DataGenerator that merges multiple DataGenerators into one.

df_from_imagenet_dir()

Create a dataframe from a directory with the imagenet directory structure.

find_lr()

Plot learning rate

fixup_target_levels_prediction_classif()

Fix target levels

get_tf_num_features()

get_tf_num_features: Get number (dimension) of tensorflow features for TabNet.

keras_reflections

Reflections mechanism for keras

make_embedding()

Create the embedding for a dataset.

make_generator_from_dataframe()

Make a DataGenerator from a data.frame or data.table

make_generator_from_task()

Make a DataGenerator from a mlr3::Task

make_generator_from_xy()

Make a DataGenerator from a x,y matrices

make_train_valid_generators()

Create train / validation data generators from a task and params

mlr3keras-package

mlr3keras: mlr3 Keras extension

mlr3keras_set_seeds() configure_session()

Set Seed for mlr3keras

reshape_data_embedding()

Reshape data for use with entity embeddings.

reshape_task_embedding()

Reshape a Task for use with entity embeddings.