# Yimeng-Zhang/feature-engineering-and-feature-selection

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

Repository: https://github.com/Yimeng-Zhang/feature-engineering-and-feature-selection
Canonical: https://ross.abutalabs.com/products/feature-engineering-and-feature-selection
Language: Jupyter Notebook
License Family: other
Topics: python, machine-learning, feature-engineering, feature-selection, feature-extraction, data-mining
Last push: 2022-09-24T11:33:22+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2831, "days_push": 1439, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1656, forks 423 (observed 2026-08-28T04:05:17.941750+00:00)

## What it is
A comprehensive guide to feature engineering and feature selection for machine learning, provided as a PDF and markdown document with Python implementations and examples. It explains the why, how, and when of each technique, mostly built on scikit-learn.

## Use cases
- learn feature engineering techniques for machine learning
- find methods to select the best features from a dataset
- get Python code examples for feature extraction
- understand pros and cons of feature selection methods
- reference guide while building an ML pipeline
- handle data problems like missing values and outliers

## When to choose
- you want a structured educational reference on feature engineering and selection
- you need copy-paste Python implementations based on scikit-learn
- you want explanations of rationale, pros, and cons of each technique

## When to avoid
- you need a production-ready installable library with maintained APIs
- you require a licensed package for commercial use (no license is provided)
- you need support for recent Python versions beyond 3.5-3.7

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, data-science, developer-tools
- domain: machine-learning, data-science, tutorials
- platform: python
- tags: feature-engineering, feature-selection, jupyter-notebook, guide, scikit-learn

## Member repositories
- Yimeng-Zhang/feature-engineering-and-feature-selection (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:17.941750+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:44:49.093276+00:00, confidence not recorded.
  - readme: https://github.com/Yimeng-Zhang/feature-engineering-and-feature-selection (fetched 2026-08-28T04:05:17.941750+00:00, sha c07e2e872387)
- Data as of 2026-08-30T08:39:29.467469+00:00.