BREAST CANCER DETECTION USING DECISION TREE CLASSIFIER

Abstract

Identification of breast cancer plays a major role in medical field nowadays. Women are facing different types of cancer and one among them is breast cancer which has severe impact. Breast cancer is of two types i.e. Malign or Benign type. Benign is given as a non-curable type of cancer and Malign is given as curable type of cancer. Breast cancer is symbolized by the modification of genes, persistent pain, changes in the measurement, change in shade (redness), and skin appearance of breasts. In the early days of identifying breast cancer is done by using different algorithms namely Support Vector Machine (SVM) algorithm ,K Nearest Neighbor (KNN) algorithm , MLP algorithm, etc., By using these algorithms the accuracy of detecting the cancer is not met the extend. Our idea is to detect the breast cancer using Decision Tree algorithm. The decision tree algorithm comes under the supervised learning technique. Our idea is to detect the breast cancer using Decision Tree algorithm. The tree algorithm comes under the supervised learning technique. The main advantage of this decision tree algorithm is identifying whether the predicted cancer is either malign or benign type by producing an 99% accuracy.