---
title: "A Hybrid Genetic Algorithm for Classification"
authors:
  - "James D. Kelly Jr."
  - "Lawrence Davis"
doi: ""
url: "https://ijcai.org/proceedings/1991/94"
pdf: "https://ijcai.org/proceedings/1991/0094.pdf"
venue: "Proceedings of the Twelfth International Joint Conference on Artificial Intelligence"
year: 1991
pages: "645-649"
track: "Learning Be Knowledge Acquisition"
keywords:
---

# A Hybrid Genetic Algorithm for Classification

James D. Kelly Jr., Lawrence Davis

*Proceedings of the Twelfth International Joint Conference on Artificial Intelligence*, pages 645-649.

## Abstract

In this paper we describe a method for hybridizing a genetic algorithm and a k nearest neighbors classification algorithm. We use the genetic algorithm and a training data set to learn real-valued weights associated with individual attributes in the data set. We use the k nearest neighbors algorithm to classify new data records based on their weighted distance from the members of the training set. We applied our hybrid algorithm to three test cases. Oassification results obtained with the hybrid algorithm exceed the perfonnance of the k nearest neighbors algorithm in all three cases.