random-forest-importances
Code to compute permutation and drop-column importances in Python scikit-learn models
MIT License
Ecosystems:
scikit-learn
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random-forest-importances
- Improve compatibility with 0.24 scikit-learn
Latest Release
Published by parrt over 3 years ago
random-forest-importances
- 1.3.6 Add title to plots, improve sklearn compatibility, add support for different correlation methods
Published by parrt almost 4 years ago
random-forest-importances
- small bug fix for 0.22 sklearn
Published by parrt over 4 years ago
random-forest-importances
- Improve bar charts for feature importances, add feature dependence heatmap
Published by parrt almost 6 years ago
- Added
plot_dependence_heatmap()to plot feature dependence heat maps - Improve feature importance plots so that the bars are always the same. You can specify a title and there is better scaling support.
- The plotting routines return
PimpVizobjects that by default render the current matplotlib image via SVG, getting a much sharper image than the default PNG. - dropcol importance was relying on OOB scores instead of the more general model scoring/metric.
- Added a stemplot version that mimics the bar chart for feature importance.
- Added precision argument to the correlation heat map function.
- Rebuilt the notebook examples and the ones that generate images for the paper.
- Added a section to the paper that shows the feature dependence heat map applied to the breast-cancer data set.
random-forest-importances
- Improve bar charts for feature importances
Published by parrt about 6 years ago
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