SIFT

SIFT is a Python feature-selection toolbox for fast filter selectors, automatic feature-count selection, stability selection, smart sampling, Boruta-style selection, grouped or time-aware permutation importance, and optional CatBoost selection.

The package is a single Python library. Public entry points are exported from sift, while advanced building blocks live under sift.selection, sift.estimators, and sift.sampling.

Quickstart

Install from the repository root:

python -m pip install -e .

Optional extras:

python -m pip install -e ".[categorical]"
python -m pip install -e ".[catboost]"
python -m pip install -e ".[test]"
python -m pip install -e ".[all]"

Run a fixed-k selector:

import pandas as pd
from sklearn.datasets import make_regression
from sift import select_mrmr, select_cefsplus

X_arr, y = make_regression(
    n_samples=500,
    n_features=30,
    n_informative=8,
    noise=0.2,
    random_state=0,
)
X = pd.DataFrame(X_arr, columns=[f"f{i}" for i in range(X_arr.shape[1])])

mrmr_features = select_mrmr(X, y, k=10, task="regression", verbose=False)
cefs_features = select_cefsplus(X, y, k=10, verbose=False)

For the full public API, examples, selector support matrix, and option details, start with DOCS.MD.

Documentation

• Full API manual
• User guide
• Troubleshooting
• Architecture and module boundaries
• Development guide
• Benchmarks
• Release tracker

Main Components

Area	Entry points
Core filters	select_mrmr, select_jmi, select_jmim, select_cefsplus, select_cefsplus_binary
Automatic k	AutoKConfig, k="auto", select_k_auto, select_k_elbow, select_k_penalized_objective
Result objects and wrappers	FilterSelectionResult, MRMRSelector, JMISelector, JMIMSelector, CEFSPlusSelector, CEFSPlusBinarySelector
Cache-backed Gaussian paths	build_cache, select_cached, FeatureCache
Sampling and stability	smart_sample, SmartSamplerConfig, StabilitySelector, stability_regression, stability_classif
Model-based importance	permutation_importance, BorutaSelector, select_boruta, select_boruta_shap, CatBoost helpers

Development

Install test dependencies and run the suite:

python -m pip install -e ".[test]"
python -m pytest -q

See docs/development.md for focused test slices, benchmarks, documentation checks, and release notes.

License

SIFT is released under the MIT License.