Machine Learning Algorithms For Breast Cancer Prediction And Diagnosis

Each year number of deaths is increasing extremely because breast cancer. It the most frequent type all cancers and major cause death in women worldwide. Any development for prediction diagnosis cancer disease capital important a healthy life. Consequently, high accuracy to update treatment aspect survivability standard patients. Machine learning techniques can bring large contribute on process early cancer, became research hotspot has been proved as strong technique. In this study, we applied five machine algorithms: Support Vector (SVM), Random Forest, Logistic Regression, Decision tree (C4.5) K-Nearest Neighbours (KNN) Breast Cancer Wisconsin Diagnostic dataset, after obtaining results, performance evaluation comparison carried out between these different classifiers. The main objective paper predict using machine-learning algorithms, find effective whit respect confusion matrix, precision. observed that vector outperformed other classifiers achieved highest (97.2%).All work done Anaconda environment based python programming language Scikit-learn library.