Feature Selection Result #160 — Analysis Report
Contents
- univariate screening (#160) completed
1. Univariate Screening
2026-09-21 02:12:36 · feature_selection
35 feature(s) passed the screen.
| task_type | regression |
|---|---|
| n_samples | 400 |
| n_features | 40 |
| target_column | PC_SHOOTMASS |
volcano
pvalue qq
Method & Provenance
- Method
- Univariate feature screening
- Engine
- Python · scikit-learn/scipy 1.8.0
- Input dataset
- gallery — cat_g_field_data_plots.csv
- Started
- 2026-09-21 02:12:36.563461
- Permanent link
- https://cat-g-omxpert.wishartlab.com/results/by-token/ddc9cb78b42f4d9c87d80959e89650af
| Parameter | Value |
|---|---|
| method | univariate_screening |
| target_col | PC_SHOOTMASS |
| fdr_threshold | 0.05 |
| derived_dataset_id | 692 |
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')