ItemArticle

Attribute optimization to improve breast cancer prediction using machine learning techniques

Title
Attribute optimization to improve breast cancer prediction using machine learning techniques
Creator
Srinivasaiah, Raghavendra; Jankatti, Santosh Kumar; Jinachandra, Niranjana Shravanabelagola; Lamani, Manjunath Ramanna; Lakshmi, Bellam Vijaya; Bhelwa, Rishita
Description
Breast cancer (BC) arises when cells grow out of control. It affects women more than men. Seeking cancer treatment can be both costly and time-consuming, with test results spanning from a few hours to several weeks. The duration of these tests depends on the number of attributes within the dataset. This research paper endeavors to optimize the dataset attributes and find the accuracy of the optimized dataset. The primary goal is to reduce features using recursive feature elimination to minimize the time taken for the test result. This work discusses the machine learning technique and the random forest (RF) algorithm, which helps determine the parameter accuracy on the Wisconsin BC diagnostic dataset. The method achieves an accuracy of 96.49% with only eighteen attributes. It has aided the healthcare industry in finding BC in less time and improving the treatment. Copyright (c) 2026 Peddireddy Venkateswara Reddy, Alaguchamy Parivazhagan. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Source
IAES International Journal of Artificial Intelligence;Volume;15;Issue;2;pp.1327-1338
Date
01-01-2026
Publisher
Institute of Advanced Engineering and Science
Subject
Attribute optimization; Breast cancer prediction; Machine learning; Random forest classifier; Wisconsin
Coverage
Srinivasaiah R., Department of Artificial Intelligence and Data Science Engineering, School of Engineering and Technology, CHRIST University, Bangalore, India; Jankatti S.K., Department of Computer Science and Technology, Dayananda Sagar University, Bangalore, India; Jinachandra N.S., Department of Mechanical Engineering, CHRIST University, Bangalore, India; Lamani M.R., Department of Computer Science and Engineering, Moodlakatte Institute of Technology, Kundapura, India; Lakshmi B.V., Department of Computer Science and Engineering, CHRIST University, Bangalore, India; Bhelwa R., Department of Computer Science and Engineering, CHRIST University, Bangalore, India
Rights
All Open Access; Gold Open Access
Relation
ISSN: 20894872;
Format
online
Language
English
Type
Article

Citation

Srinivasaiah, Raghavendra; Jankatti, Santosh Kumar; Jinachandra, Niranjana Shravanabelagola; Lamani, Manjunath Ramanna; Lakshmi, Bellam Vijaya; Bhelwa, Rishita, “Attribute optimization to improve breast cancer prediction using machine learning techniques,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/23080.

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