In Recent Years, The Most Prevalent Form Of Cancer Diagnosed In Women Across The Globe Is Breast Cancer. It Develops In The Breast Tissue And Is One Of The Most Frequent Causes Of Womens Death. This Cancer Can Be Cured If It Is Diagnosed At Preliminary Stage. Malignant And Benign Are Two Types Of Tumor Found In Case Of Breast Cancer. Malignant Tumors Are Deadly As Their Rate Of Growth Is Much Higher Than Benign Tumors. So, Early Identification Of Tumor Type Is Pivotal For The Appropriate Treatment Of A Patient Having Breast Cancer. In This Work, Wisconsin Breast Cancer Dataset Has Been Used Which Was Collected From UCI Repository. Our Goal Is To Analyze The Dataset And Evaluate The Performance Of Various Machine Learning Algorithms For Predicting Breast Cancer.
