On the use of multi-objective evolutionary classifiers for breast cancer detection.

ABSTRACT:

Purpose

Breast cancer is one of the most common tumours in women, nevertheless, it is also one of the cancers that is most usually treated. As a result, early detection is critical, which can be accomplished by routine mammograms. This paper aims to describe, analyze, compare and evaluate three image descriptors involved in classifying breast cancer images from four databases.

Approach

Multi-Objective Evolutionary Algorithms (MOEAs) prove themselves as being efficient methods for selection and classification problems. This paper aims to study combinations of well-known classification objectives in order to compare the results of their application in solving very specific learning problems. The experimental results undergo empirical analysis which is supported by a statistica

SUBMITTER: Diosan L 

PROVIDER: S-EPMC9295958 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature