Feature Selection Result #163 — Analysis Report
Contents
- univariate screening (#163) completed
1. Univariate Screening
2026-09-21 02:13:46 · feature_selection
29 feature(s) passed the screen.
| task_type | regression |
|---|---|
| n_samples | 393 |
| n_features | 33 |
| target_column | PC_SHOOTMASS |
volcano
pvalue qq
Method & Provenance
- Method
- Univariate feature screening
- Engine
- Python · scikit-learn/scipy 1.8.0
- Input dataset
- gallery — catg_example_01_forage_biomass.csv
- Started
- 2026-09-21 02:13:46.233864
- Permanent link
- https://cat-g-omxpert.wishartlab.com/results/by-token/6464413f754e4693bdfa3aaf528d0baf
| Parameter | Value |
|---|---|
| method | univariate_screening |
| target_col | PC_SHOOTMASS |
| fdr_threshold | 0.05 |
| derived_dataset_id | 696 |
Command history
# python from scipy import stats # python r, p = stats.pearsonr(x_feature, y_target) # python stat, p = stats.kruskal(*groups) # per feature # python fdr = statsmodels.stats.multitest.multipletests(p_values, method='fdr_bh')