Univariate Screening run #163 · feature_selection
regression
task type
393
n samples
33
n features
PC_SHOOTMASS
target column
completed
status
2026-09-21 02:13
created
Figures
Screening volcano
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P-value QQ plot
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Method & Provenance
- Method
- Univariate feature screening
- Method key
univariate_screening(result type:feature_selection, result #163)- Engine
- Python · scikit-learn/scipy v1.8.0
- Dataset(s)
- #694 gallery — catg_example_01_forage_biomass.csv
- Status
- completed
- Permanent link
- https://cat-g-omxpert.wishartlab.com/results/by-token/6464413f754e4693bdfa3aaf528d0baf Bookmark or share this URL — it does not depend on your session.
- Created
- 2026-09-21 02:13:46.233864
Parameters used
| Parameter | Value |
|---|---|
method
| univariate_screening |
target_col
| PC_SHOOTMASS |
fdr_threshold
| 0.05 |
derived_dataset_id
| 696 |
Execution trace
Reconstructed from the parameters stored with this result — represents the Python/R calls the analysis service made.
from scipy import stats
r, p = stats.pearsonr(x_feature, y_target)
stat, p = stats.kruskal(*groups) # per feature
fdr = statsmodels.stats.multitest.multipletests(p_values, method='fdr_bh')