Paper Title :Comparison Of Data Mining Algorithms For Mammogram Classification

Author :Monika Hedawoo, Abhinandan Jaisawal, Nishita Mehta

Article Citation :Monika Hedawoo ,Abhinandan Jaisawal ,Nishita Mehta , (2016 ) " Comparison Of Data Mining Algorithms For Mammogram Classification " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 31-34, Volume-4,Issue-7

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.

Type : Research paper

Published : Volume-4,Issue-7

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