pre-release v0.7.4: support annotations (feature/sample), stratified holdout & logic improvements#37
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…atified CV Feature Annotations: - Enable reading of annotation files. - Add prior weights to influence feature occurrence in initial GA population. - Implement user-customized feature penalties (weighted via param.general.user_feature_penalties_weight). - Add support for additional tags to enhance result visualization. Sample Annotations: - Enable reading of sample annotation files. - Implement cross-validation stratification based on both classes and annotation columns. CLI & visual improvements: - Add `--export-param` flag to export parameters from previous experiments. - Improve rendering of threshold CI. Fixes: - fix(fbm): resolve critical bug where the entire population was used instead of the FBM in CV mode. - style: correct terminology 'G-means' to 'G-mean'.
…lways enable niche filtering
- Add param.data.holdout_ratio and use it in run to perform an internal train/holdout split when no external Xtest/Ytest are provided. - Implement Data::train_test_split with class and optional annotation stratification, plus unit tests for size, class balance, annotations and reproducibility. - Extend GA and Beam Qin2014 E2E tests to cover internal holdout and to assert that external Xtest/Ytest override holdout_ratio while preserving identical train/test samples and labels.
eprifti
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Feb 24, 2026
pre-release v0.7.4: support annotations (feature/sample), stratified holdout & logic improvements
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Add support for feature and sample annotations (prior weights, penalties, stratified CV), implement native holdout train/test split with stratification, fix critical FBM population bug in CV mode, refactor Jaccard filtering using model groups, add
--export-paramCLI flag, improve threshold CI rendering, and add GPL-3.0 license.