• Ranjeet Kumar
• Vijay Kumar Singh

The death due to breast cancer is increasing day by day. Survival rate can be increased by modern treatment methods, if cancer is detected at early stage with high accuracy. Several parameters of patients are stored in cancer dataset and all parameters are not equally important to predict cancer. In this article, different classifier indicators are compared with and without reduced attributes of Wisconsin Breast Cancer (WBC) dataset, by applying a feature selection algorithm. It was found that reduced attribute cancer dataset has better accuracy than original cancer dataset.

Breast cancer, feature selection, machine learning classifier

"Selected Feature Based Improvements in Breast Cancer Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.a540-a543, March-2024, Available :http://www.jetir.org/papers/JETIR2403072.pdf

"Selected Feature Based Improvements in Breast Cancer Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppa540-a543, March-2024, Available at : http://www.jetir.org/papers/JETIR2403072.pdf