Implementing Machine Learning Techniques on WDBC Datasets with Limited and Complete Features: A Comparative Analysis

Abstract

Cancer is one of the most lethal illnesses. Although there are various types of cancer, breast cancer is the most common, particularly among women worldwide. It has been shown that detecting cancer at an early stage increases the odds of survival. This is related to the fact that treatment starts early. As a result, this region requires specific care. Machine learning technologies are gaining traction in the medical profession. Many hardware and software businesses have lately used machine learning methods to get high-quality solutions. In this paper, ML methods were used for the WDBC dataset. A comparison study is performed, demonstrating the differences in results achieved after applying the identical algorithms to WDBC datasets with limited and comprehensive characteristics. Comparison parameters like accuracy, f1- score, and recall are used to demonstrate the performance of the models.