Assessment of the Performance of MLP & Hierarchical Clustering Method in the Prediction of Breast Cancer

Authors

  • Bhattacharya J Computer Science and Engineering, JIS College of Engineering, JIS University, Kalyani, India
  • Rakshit P Computer Science and Engineering, JIS College of Engineering, JIS University, Kalyani, India
  • Roy A Computer Science and Engineering, JIS College of Engineering, JIS University, Kalyani, India
  • Singh D Computer Science and Engineering, JIS College of Engineering, JIS University, Kalyani, India
  • Dalui D Computer Science and Engineering, JIS College of Engineering, JIS University, Kalyani, India

Keywords:

Soft Computing, Breast Cancer, Benign, Malignant, Hierarchical Clustering Method,, Multilayer Perceptron

Abstract

Breast cancer is such a type of cancer which can leads to the death of women .in this type of cancer there is excessive growth of cells of the breast tissue are done. Lump, pain or sore, bloody nipple, and change in size are being visible for the case of breast cancer. Breast cancer took places when the tissues of the breast are not in a normal manner and not divided in a proper way. Those abnormal cells make clotted mass tissues, which therefore that becomes a tumor. There are two types of tumors, one is benign, which are not cancerous and that no becomes the cause of anyone‘s death .Another type of tumor is Malignant tumor, that is cancerous and very harmful. The second type of tumor can lead to the death. Soft computing techniques are become popular for the case of medical disease diagnosis and also for the prediction. In this paper we combine the Hierarchical Clustering Method and Multilayer Perceptron to predict of the breast cancer .The accuracy of the proposed methods is 81% for the clustering method and 94% for Multilayer Perceptron.

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Published

2020-02-28

How to Cite

[1]
J. V, P. V, A. Roy, D. Singh, and Debolina Dalui, “Assessment of the Performance of MLP & Hierarchical Clustering Method in the Prediction of Breast Cancer”, Int. J. Comp. Sci. Eng., vol. 8, no. 1, pp. 55–58, Feb. 2020.

Issue

Vol. 8 No. 1 (2020): IJCSE Special Issue Feb Edition

Section

Research Article

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