Open AccessResearch of Feature Selection Methods to Predict Breast Cancer
Author(s) -
K Venkateswararao,
L. MaryGladence
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1268.0982s1119
Subject(s) - feature selection , breast cancer , computer science , feature (linguistics) , selection (genetic algorithm) , feature extraction , artificial intelligence , data mining , cancer , pattern recognition (psychology) , disease , machine learning , medicine , linguistics , philosophy
Human health is most important than anything in the world, one should take care of it. Among various disease, cancer is the most terrible and deadly disease, so it is necessary to predict such disease in early stage. In this paper different feature selection methods used for feature extraction with different feature classification methods to identify the breast cancer. Breast cancer data is taken from UCI repository and is processed using WEKA tool and proposed techniques are applied to classify data accurately. This study well defines that data mining approach is suitable for predicting breast cancer.