# Feature Selection

Skill · Data Science, Analytics and AI/ML

Canonical page: https://career.thegoodapps.co/skills/feature-selection

Feature selection is a machine learning technique for choosing the most relevant subset of input variables from a dataset to use in model training, discarding redundant or irrelevant features. Methods include filter approaches (statistical tests), wrapper approaches (like recursive feature elimination), and embedded methods (like LASSO regularization). It helps reduce overfitting, improve model interpretability, and decrease computational cost, and is used by data scientists across domains like finance, healthcare, and marketing analytics.

Related skills: [Machine Learning](https://career.thegoodapps.co/skills/machine-learning), [Feature Engineering](https://career.thegoodapps.co/skills/feature-engineering), [Dimensionality Reduction](https://career.thegoodapps.co/skills/dimensionality-reduction), [scikit-learn](https://career.thegoodapps.co/skills/scikit-learn)

## Open roles requiring Feature Selection (0)

None of the roles we have read name this skill yet. A large share of the visible corpus has not been parsed for skills, so this is at least as likely to be our backlog as the market's verdict.