A Cross Design for Breast Cancer Prediction

Breast cancer in women’s becoming the serious cause moving to the morbidity and the mortality worldwide. This paper aims to design the hybrid model using various machine learning classification algorithms like k-Nearest Neighbor (KNN), Support Vector Classifier (SVC), Logistic Regression (LR), and Gaussian Naïve Bayes to predict the breast cancer. Moreover, the accuracy has been increased with the varied classifiers and decides the precision using the f1- Score, and Jaccard index. The data set is of Kaggle is used to train the model and then test them using the machine learning algorithms. The proposed model is also prepared forum foreseen data in future by validating using K-fold Cross Validation Technique. By Random Forest Classifier (RFC) model exhibit the significant performance.