---
title: Feature Engineering
description: "Feature engineering is the addition or construction of supplementary features to a dataset to improve model performance. Some of the approaches are outlined below. **Enrichment**: supplementing a dataset with additional data from external sources, e.g., adding customer details to a…"
url: "https://sdscope.com/doc/feature-engineering/"
updated: "2022-06-03"
category: 6. Data Preparation
---

# Feature Engineering

Feature engineering is the addition or construction of supplementary features to a dataset to improve model performance. Some of the approaches are outlined below.

**Enrichment**: supplementing a dataset with additional data from external sources, e.g., adding customer details to a dataset containing phone usage

**Aggregations:** calculating counts, sum, difference, average, most recent, minimum, maximum, range of a feature

**Extracting features:** e.g., extracting day of week (Monday, Tuesday, etc), time of day (morning, afternoon, etc) from datetime values, or extracting gender from name

**Feature interaction:** combining two or more features to produce a new effect or behavior of the original features. Aristotle's predicate "The whole is greater than the sum of its parts," applies here. For example, calculating body-mass index from weight and height, or computing polynomial combinations between features to enable linear methods to detect non-linear relationship between the features and the target.

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