MACHINE LEARNING TECHNIQUES FOR THE DIAGNOSIS OF BREAST CANCER

ABSTRACT:- Now-a-days, breast cancer is a disease that significantly impacts women. Breast cancerhas surpassed lung cancer as the most often reported cancer in women worldwide, according to theInternational Agency for Research on Cancer (IARC) in December 2020. If cancer is found in the earlystages, the likelihood that someone will survive is increased.This paper recap the survey on breast cancerdiagnosis using various Machine Learning (ML) methods, which are used to boost the accuracypredicting cancer. The paper shows the data visualisation and performance differentiations betweendifferent ML algorithms like, Random Forest (RF), Naive Bayes (NB) ,Multilayer Perceptron, DecisionTree (DT), K- Nearest Neighbours (KNN), and Logistic Regression (LR). The major goal is to evaluatethe model's performance, and tools like recall, F1-score, precision, and accuracy are employed to do so.