hetcorFS
1.0.1Unsupervised Feature Selection using the Heterogeneous Correlation Matrix
Overview
Unsupervised multivariate filter feature selection using the UFS-rHCM or UFS-cHCM algorithms based on the heterogeneous correlation matrix (HCM). The HCM consists of Pearson's correlations between numerical features, polyserial correlations between numerical and ordinal features, and polychoric correlations between ordinal features. Tortora C., Madhvani S., Punzo A. (2025). "Designing unsupervised mixed-type feature selection techniques using the heterogeneous correlation matrix." International Statistical Review doi:10.1111/insr.70016. This work was supported by the National Science foundation NSF Grant N 2209974 (Tortora) and by the Italian Ministry of University and Research (MUR) under the PRIN 2022 grant number 2022XRHT8R (CUP: E53D23005950006), as part of ‘The SMILE Project: Statistical Modelling and Inference to Live the Environment’, funded by the European Union – Next Generation EU (Punzo).
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Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 80%
- Documented parameters
- 97%
- Return-value docs
- 100%
- References docs
- 83%
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Code & Tests
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People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.0.1Latest
- 1.02025-10-28
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-10-28
- Total releases
- 2 / 1 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 6.9 KB / 1 file
- Download size
- 16 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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