Decision Tree based Multi-Classifier Model for Breast Cancer Screening System
Breast cancer is recognized as most commonly diagnosed life threatening cancer among women. Breast cancer is a form of cancer which develops in mammary glands in the form of invasive tumor. According to WHO(World Health Organization), due to the above, almost 6,27,000 women died in the year 2018. By implementing Machine learning algorithms and techniques, researches have been undertaken to predict the threats of breast cancer. In this paper, the proposed work is presented with the integrated probability results of two decision tree based classifiers: J48 and Random forest algorithms. Finally the model has proven with the better accuracy, precision and recall with preprocessing when compared with unprocessed data.