Analysis of Machine Learning Algorithms for prediction and classification of Breast Cancer

The most common disease that can be seen in women is breast cancer.According to 2021 statistics it was found that 281,550 new cancer cases were discovered in US.Due to rapid increase in death because to breast cancer, there is a need to find an effective solution to this problem.As we know that ML algorithms helps in providing solution with better accuracy.In this paper we have applied several ML algorithms like DT (Decision tree), RF (Random Forest) Classifier, NB (Naïve Bayes) classifier, KNN, ADABOOST, GBDT, SVM (Support Vector Machine), SGD, RF (Random Forest) Classifier.And we have applied feature selection to extract best attributes so that ML classifier can provide better accuracy to our model and helps in saving life of many peoples.The accuracy of GDBT is 97%, SVM classifier is 96.4% , ADABOOST is 96%, SGD is 94% , RF classifier is 92%, KNN is 90% DT classifier 90% and NB classifier 90% .Out of all GBDT provides best accuracy which is 97%.