Hybridization of ML techniques for predicting Breast Cancer

Breast cancer is one of the most prevalent forms of cancer among Indian residents. Breast cancer ranks fourth in the top ten cancers in America. Every four minutes, a woman in India is diagnosed with breast cancer, according to the statistics. Women in rural and urban India are more likely to get breast cancer than in the past. One in twenty-eight Indian women will be diagnosed with breast cancer. Urban women are more likely to suffer from it (1 in 22) than rural women (1 in 60). According to breast cancer statistics from 2018, there were 1,62,468 newly reported cases and 87,090 fatalities. These deaths can be avoided if cancerous cells are detected early. This research describes a strategy for detecting breast cancer using ML techniques. The primary goal is to predict breast cancer from the benchmarked input dataset, which consists of the information about Benign and Malignant based on symptoms. The system is built using two Algorithms Logistic Regression and Decision Tree. The obtained accuracy of the proposed method was 96.8%, whereas the precision score were found to be 94.5%.