feat: regression support — Data.y Vec<u8> → Vec<f64>, Spearman/RMSE fitness#76
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feat: regression support — Data.y Vec<u8> → Vec<f64>, Spearman/RMSE fitness#76
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All class labels (0/1/2) are now stored as f64 (0.0/1.0/2.0). Continuous y values (gene_count, etc.) can now be loaded for regression. Changes across 10 files: - data.rs: field type, loading, feature selection, class operations - individual.rs: evaluation, confusion matrix, threshold optimization - population.rs: fitness computation, removed y_f64 intermediaries - utils.rs: all metric functions, bootstrap, stratification - cv.rs: fold splitting, stratification - voting.rs: confusion matrix, predictions - bayesian_mcmc.rs: posterior computation - csv_report.rs: metric export - lib.rs: remove_class calls 776 lib tests pass. Closes #15
…d feature selection - Regression mode auto-detected from fit function (spearman/rmse/mutual_information) - Feature selection bypasses class-based tests, uses prevalence only - Tested on wetlab_protocol gene_count: SA finds Spearman=0.164 with k=15 Known limitation: display still shows AUC/sensitivity/specificity (all 0.0 for regression). The fit value correctly shows the Spearman correlation. Closes #15
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Summary
Data.yfromVec<u8>toVec<f64>across 10 source filesTest
Known limitation
Display still shows AUC/sensitivity/specificity (0.0 for regression) — needs regression-specific display
Closes #15