DOIONLINE

DOIONLINE NO - IJEEDC-IRAJ-DOIONLINE-5133

Publish In
International Journal of Electrical, Electronics and Data Communication (IJEEDC)-IJEEDC
Journal Home
Volume Issue
Issue
Volume-4,Issue-7  ( Jul, 2016 )
Paper Title
Comparison Of Data Mining Algorithms For Mammogram Classification
Author Name
Monika Hedawoo, Abhinandan Jaisawal, Nishita Mehta
Affilition
Department of Information Technology, SRM University, Chennai, Tamil Nadu
Pages
31-34
Abstract
This paper describes a breast cancer classification performance trade-off analysis using two computational intelligence system. The proposed system has been implemented in four stages: (a) Region of interest (ROI) which identifies suspicion regions, (b) feature extraction stage locally processed image (ROI) to compute important features of each breast cancer. (c) Feature selection stage by using forward stepwise linear regression method (FSLR). (d) Classification stage which classifies between cancer and non-cancer case. In the classification stage we are applying two computational intelligence paradigms. K- Nearest Neighbor and Naïve Bayes Algorithm are used for classification of data whether it is cancer or non- cancer. Keywords— Naïve Bayes, k- Nearest Neighbor, Region of Interest, Feature Extraction.
  View Paper