文件名称:gcforest
介绍说明－－下载内容均来自于网络，请自行研究使用
使用深度随机森林实现对数据的分类，无论数据特征是数值型的还是符号型的。(Using a deep random forest to implement the classification of data, whether the data features are numerical or symbolic.)
相关搜索： 深度随机森林
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下载文件列表
| 文件名 | 大小 | 更新时间 |
|---|---|---|
| Deep Forest Towards An Alternative to Deep Neural Networks.pdf | 2058158 | 2017-11-08 |
| datasets | ||
| datasets\gtzan | ||
| datasets\gtzan\get_data.sh | 1033 | 2017-05-26 |
| datasets\gtzan\splits | ||
| datasets\gtzan\splits\blues.train | 1680 | 2017-05-22 |
| datasets\gtzan\splits\blues.trainval | 2400 | 2017-05-22 |
| datasets\gtzan\splits\blues.val | 720 | 2017-05-22 |
| datasets\gtzan\splits\classical.train | 2240 | 2017-05-22 |
| datasets\gtzan\splits\classical.trainval | 3200 | 2017-05-22 |
| datasets\gtzan\splits\classical.val | 960 | 2017-05-22 |
| datasets\gtzan\splits\country.train | 1960 | 2017-05-22 |
| datasets\gtzan\splits\country.trainval | 2800 | 2017-05-22 |
| datasets\gtzan\splits\country.val | 840 | 2017-05-22 |
| datasets\gtzan\splits\disco.train | 1680 | 2017-05-22 |
| datasets\gtzan\splits\disco.trainval | 2400 | 2017-05-22 |
| datasets\gtzan\splits\disco.val | 720 | 2017-05-22 |
| datasets\gtzan\splits\genre.train | 17360 | 2017-05-22 |
| datasets\gtzan\splits\genre.trainval | 24800 | 2017-05-22 |
| datasets\gtzan\splits\genre.val | 7440 | 2017-05-22 |
| datasets\gtzan\splits\genres.trainval | 22800 | 2017-05-22 |
| datasets\gtzan\splits\hiphop.train | 1820 | 2017-05-22 |
| datasets\gtzan\splits\hiphop.trainval | 2600 | 2017-05-22 |
| datasets\gtzan\splits\hiphop.val | 780 | 2017-05-22 |
| datasets\gtzan\splits\jazz.train | 1540 | 2017-05-22 |
| datasets\gtzan\splits\jazz.trainval | 2200 | 2017-05-22 |
| datasets\gtzan\splits\jazz.val | 660 | 2017-05-22 |
| datasets\gtzan\splits\metal.train | 1680 | 2017-05-22 |
| datasets\gtzan\splits\metal.trainval | 2400 | 2017-05-22 |
| datasets\gtzan\splits\metal.val | 720 | 2017-05-22 |
| datasets\gtzan\splits\pop.train | 1400 | 2017-05-22 |
| datasets\gtzan\splits\pop.trainval | 2000 | 2017-05-22 |
| datasets\gtzan\splits\pop.val | 600 | 2017-05-22 |
| datasets\gtzan\splits\reggae.train | 1820 | 2017-05-22 |
| datasets\gtzan\splits\reggae.trainval | 2600 | 2017-05-22 |
| datasets\gtzan\splits\reggae.val | 780 | 2017-05-22 |
| datasets\gtzan\splits\rock.train | 1540 | 2017-05-22 |
| datasets\gtzan\splits\rock.trainval | 2200 | 2017-05-26 |
| datasets\gtzan\splits\rock.val | 660 | 2017-05-22 |
| datasets\uci_adult | ||
| datasets\uci_adult\features | 1156 | 2017-05-22 |
| datasets\uci_adult\get_data.sh | 1119 | 2017-05-26 |
| datasets\uci_letter | ||
| datasets\uci_letter\get_data.sh | 1063 | 2017-05-26 |
| datasets\uci_semg | ||
| datasets\uci_semg\get_data.sh | 1111 | 2017-05-26 |
| datasets\uci_yeast | ||
| datasets\uci_yeast\get_data.sh | 1039 | 2017-05-26 |
| datasets\uci_yeast\yeast.label | 68 | 2017-05-22 |
| lib | ||
| lib\gcforest | ||
| lib\gcforest\cascade | ||
| lib\gcforest\cascade\cascade_classifier.py | 13270 | 2017-05-25 |
| lib\gcforest\cascade\__init__.py | ||
| lib\gcforest\datasets | ||
| lib\gcforest\datasets\cifar10.py | 2482 | 2017-05-25 |
| lib\gcforest\datasets\ds_base.py | 3433 | 2017-05-25 |
| lib\gcforest\datasets\ds_pickle.py | 2079 | 2017-05-25 |
| lib\gcforest\datasets\ds_pickle2.py | 1507 | 2017-05-25 |
| lib\gcforest\datasets\gtzan.py | 4512 | 2017-05-25 |
| lib\gcforest\datasets\imdb.py | 3771 | 2017-05-25 |
| lib\gcforest\datasets\mnist.py | 2408 | 2017-05-25 |
| lib\gcforest\datasets\olivetti_face.py | 2072 | 2017-05-25 |
| lib\gcforest\datasets\uci_adult.py | 4180 | 2017-05-25 |
| lib\gcforest\datasets\uci_letter.py | 2057 | 2017-05-25 |
| lib\gcforest\datasets\uci_semg.py | 3075 | 2017-05-25 |
| lib\gcforest\datasets\uci_yeast.py | 2862 | 2017-05-25 |
| lib\gcforest\datasets\__init__.py | 2247 | 2017-05-25 |
| lib\gcforest\data_cache.py | 5599 | 2017-05-25 |
| lib\gcforest\estimators | ||
| lib\gcforest\estimators\base_estimator.py | 5484 | 2017-05-25 |
| lib\gcforest\estimators\est_utils.py | 1937 | 2017-05-25 |
| lib\gcforest\estimators\kfold_wrapper.py | 8171 | 2017-05-25 |
| lib\gcforest\estimators\sklearn_estimators.py | 2598 | 2017-05-25 |
| lib\gcforest\estimators\__init__.py | 1890 | 2017-05-25 |
| lib\gcforest\exp_utils.py | 6649 | 2017-05-25 |
| lib\gcforest\fgnet.py | 7098 | 2017-05-25 |
| lib\gcforest\layers | ||
| lib\gcforest\layers\base_layer.py | 2730 | 2017-05-25 |
| lib\gcforest\layers\fg_concat_layer.py | 2669 | 2017-05-25 |
| lib\gcforest\layers\fg_pool_layer.py | 3976 | 2017-05-25 |
| lib\gcforest\layers\fg_win_layer.py | 6992 | 2017-05-25 |
| lib\gcforest\layers\__init__.py | 1785 | 2017-05-25 |
| lib\gcforest\utils | ||
| lib\gcforest\utils\audio_utils.py | 1885 | 2017-05-22 |
| lib\gcforest\utils\cache_utils.py | 107 | 2017-05-22 |
| lib\gcforest\utils\config_utils.py | 1834 | 2017-05-24 |
| lib\gcforest\utils\debug_utils.py | 219 | 2017-05-22 |
| lib\gcforest\utils\log_utils.py | 1361 | 2017-05-22 |
| lib\gcforest\utils\metrics.py | 923 | 2017-05-24 |
| lib\gcforest\utils\win_utils.py | 2886 | 2017-05-24 |
| lib\gcforest\utils\__init__.py | ||
| lib\gcforest\__init__.py | ||
| models | ||
| models\cifar10 | ||
| models\cifar10\gcforest | ||
| models\cifar10\gcforest\fg-tree500-depth100-3folds-ca.json | 2877 | 2017-05-26 |
| models\cifar10\gcforest\fg-tree500-depth100-3folds.json | 3742 | 2017-05-26 |
| models\gtzan | ||
| models\gtzan\gcforest |