IMPROVED CLASSIFICATION OF BREAST CANCER DATA USING HYBRID TECHNIQUES

R. Senkamalavalli, Dr.T. Bhuvaneswari

Abstract


Breast cancer is the second leading cancer for women in developed countries including India. Many new cancer detection and treatment approaches were developed. The most effective way to reduce breast cancer deaths is detect it earlier. The frequent occurrence of breast cancer and its serious consequences have attracted world wide attention in recent years. Problems such as low rate of accuracy and poor self-adaptability still exist in traditional diagnosis. In order to solve these problems, an Ada Boost-SVM classification algorithm, Combined with k-means is proposed in this research for the early diagnosis of breast cancer. The effectiveness of the proposed methods are examined by calculating its accuracy, confusion matrix which give important clues to the physicians for early diagnosis of breast cancer.

Keywords


kmeans,support vector machine,adaboost,breast cancer

Full Text:

PDF


DOI: https://doi.org/10.26483/ijarcs.v8i8.4805

Refbacks

  • There are currently no refbacks.




Copyright (c) 2017 International Journal of Advanced Research in Computer Science