| Name | Version | Summary | date |
| fgclustering |
1.1.1 |
Forest-Guided Clustering - Explainability method for Random Forest models. |
2024-11-19 17:13:43 |
| random-forest-mc |
1.2.0 |
This project is about use Random Forest approach using a dynamic tree selection Monte Carlo based. |
2024-11-17 13:28:31 |
| brif |
1.4.5 |
Build decision trees and random forests for classification and regression. |
2024-10-15 19:26:10 |
| DumME |
0.1.0 |
Mixed Effects Dummy Model |
2024-01-30 08:08:33 |
| tulia |
0.2.1 |
numpy based machine learning package with sklearn-like API |
2024-01-12 03:38:17 |
| treesmoothing |
0.0.3 |
Bayesian post-hoc regularization for random forests |
2023-12-20 11:43:46 |
| randomForestUltra |
0.5.0 |
2023-11-09 11:23:56It supports multi-objective variable and multi-fold random forest, and can calculate P value through random permutation. |
2023-11-09 03:25:37 |
| AdvancedAnalytics |
1.39 |
Python support for 'The Art and Science of Data Analytics' |
2023-03-31 00:09:38 |
| prfr |
0.2.4 |
Probabilitic random forest regression algorithm |
2023-01-25 05:54:07 |
| cubrif |
1.4.3 |
Build random forests using CUDA GPU. |
2023-01-15 01:04:34 |