Performance analysis of machine learning algorithms for breast cancer prediction

This paper presents machine learning algorithms for predicting different stages of breast cancer tumour such as benign and malignant. Machine learning (ML) models such as Logistic regression (LR), Decision tree (DT), Naive Bayes (NB), Support vector machine (SVM), K-nearest neighbour (KNN), Random Forest (RF) and XG Boost (XGB) used for predicting different stages of breast cancer. The Breast cancer data is collected from UCI machine learning Repository, this data is used training and testing the machine algorithms. Performance and evaluation of machine learning algorithms using confusion matrix and metrics are used Accuracy, Precision, Recall and f1-score. Support vector machine (SVM) performed better result of metrics score to compared with other machine learning algorithms.