Tree-based latest algorithm gc forest, performance can be achieved with the depth of learning comparable to the degree.

datasets
datasets\gtzan
datasets\gtzan\get_data.sh
datasets\gtzan\splits
datasets\gtzan\splits\blues.train
datasets\gtzan\splits\blues.trainval
datasets\gtzan\splits\blues.val
datasets\gtzan\splits\classical.train
datasets\gtzan\splits\classical.trainval
datasets\gtzan\splits\classical.val
datasets\gtzan\splits\country.train
datasets\gtzan\splits\country.trainval
datasets\gtzan\splits\country.val
datasets\gtzan\splits\disco.train
datasets\gtzan\splits\disco.trainval
datasets\gtzan\splits\disco.val
datasets\gtzan\splits\genre.train
datasets\gtzan\splits\genre.trainval
datasets\gtzan\splits\genre.val
datasets\gtzan\splits\genres.trainval
datasets\gtzan\splits\hiphop.train
datasets\gtzan\splits\hiphop.trainval
datasets\gtzan\splits\hiphop.val
datasets\gtzan\splits\jazz.train
datasets\gtzan\splits\jazz.trainval
datasets\gtzan\splits\jazz.val
datasets\gtzan\splits\metal.train
datasets\gtzan\splits\metal.trainval
datasets\gtzan\splits\metal.val
datasets\gtzan\splits\pop.train
datasets\gtzan\splits\pop.trainval
datasets\gtzan\splits\pop.val
datasets\gtzan\splits\reggae.train
datasets\gtzan\splits\reggae.trainval
datasets\gtzan\splits\reggae.val
datasets\gtzan\splits\rock.train
datasets\gtzan\splits\rock.trainval
datasets\gtzan\splits\rock.val
datasets\uci_adult
datasets\uci_adult\features
datasets\uci_adult\get_data.sh
datasets\uci_letter
datasets\uci_letter\get_data.sh
datasets\uci_semg
datasets\uci_semg\get_data.sh
datasets\uci_yeast
datasets\uci_yeast\get_data.sh
datasets\uci_yeast\yeast.label
lib
lib\gcforest
lib\gcforest\cascade
lib\gcforest\cascade\cascade_classifier.py
lib\gcforest\cascade\__init__.py
lib\gcforest\datasets
lib\gcforest\datasets\cifar10.py
lib\gcforest\datasets\ds_base.py
lib\gcforest\datasets\ds_pickle.py
lib\gcforest\datasets\ds_pickle2.py
lib\gcforest\datasets\gtzan.py
lib\gcforest\datasets\imdb.py
lib\gcforest\datasets\mnist.py
lib\gcforest\datasets\olivetti_face.py
lib\gcforest\datasets\uci_adult.py
lib\gcforest\datasets\uci_letter.py
lib\gcforest\datasets\uci_semg.py
lib\gcforest\datasets\uci_yeast.py
lib\gcforest\datasets\__init__.py
lib\gcforest\data_cache.py
lib\gcforest\estimators
lib\gcforest\estimators\base_estimator.py
lib\gcforest\estimators\est_utils.py
lib\gcforest\estimators\kfold_wrapper.py
lib\gcforest\estimators\sklearn_estimators.py
lib\gcforest\estimators\__init__.py
lib\gcforest\exp_utils.py
lib\gcforest\fgnet.py
lib\gcforest\layers
lib\gcforest\layers\base_layer.py
lib\gcforest\layers\fg_concat_layer.py
lib\gcforest\layers\fg_pool_layer.py
lib\gcforest\layers\fg_win_layer.py
lib\gcforest\layers\__init__.py
lib\gcforest\utils
lib\gcforest\utils\audio_utils.py
lib\gcforest\utils\cache_utils.py
lib\gcforest\utils\config_utils.py
lib\gcforest\utils\debug_utils.py
lib\gcforest\utils\log_utils.py
lib\gcforest\utils\metrics.py
lib\gcforest\utils\win_utils.py
lib\gcforest\utils\__init__.py
lib\gcforest\__init__.py
models
models\cifar10
models\cifar10\gcforest
models\cifar10\gcforest\fg-tree500-depth100-3folds-ca.json
models\cifar10\gcforest\fg-tree500-depth100-3folds.json
models\gtzan
models\gtzan\gcforest
models\gtzan\gcforest\ca-tree500-n4x2-3folds.json

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