Year: 2024
Type: preprint
Abstract: As the field of data analysis grows rapidly due to the large amounts of data being generated, effective data classification has become increasingly important. This paper introduces the RUle Mutation Classifier (RUMC), which represents a significant improvement over the Rule Aggregation ClassifiER (RACER). RUMC uses innovative rule mutation techniques based on evolutionary methods to improve classification accuracy. In tests with forty datasets from OpenML and the UCI Machine Learning Repository, RUMC consistently outperformed twenty other well-known classifiers, demonstrating its ability to uncover valuable insights from complex data.
Source: arXiv (Cornell University)
Author: Mokhtari, Melvin
Institution: McMaster University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4405300842