1st International Conference on Intelligent Data Analysis and Applications (IDAA 2026)
Book ChapterStatistical Test-Driven Feature Curation for Resilient Breast Carcinoma Detection via Machine-Learning Methodologies
Mostofa Tanvir Sourov, Mim Akter Khadiza, Antu Roy Chowdhury, Md Abu Ismail Siddique
This study analyzes the Breast Cancer Wisconsin dataset using Chi-square, Fisher’s exact, and Student’s t-tests across six machine learning classifiers. The SVM classifier combined with Chi-square or Fisher’s score achieved a peak performance of 98.25% accuracy, proving...
Breast CancerCarcinoma DetectionChi-Square TestFeature Selection
