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Data Mining on Classifiers Prophecy of Breast Cancer Tissues


Affiliations
1 School of CSA, REVA University, India
 

The expression "breast cancer" includes to a harmful tumour that has created from cells in the breast. Disease happens because of transformations, or anomalous changes, in the qualities in charge of controlling the development of cells and keeping them solid. The qualities are in every cell's core, which goes about as the "control room" of every cell inside the body.The utilization of machine learning and data mining techniques strategies have transformed the entire procedure of breast cancer growth.

There are a few order calculations like-Naive Bayes, K-Star, Multiclass, Decision Table, Hoeffding Tree. Highlight Selection is the path towards picking a subset of noteworthy highlights (factors, markers) for use in presentation advancement and the part assurance computation. The results show that part decision can improve the precision of classifiers.


Keywords

Breast Cancer, Classifiers, Naïve Bayes, K-Star, Hoeffding Tree, Hybrid classifier.
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  • https://training.seer.cancer.gov/breast/intro/

  • https://www.hindustantimes.com/health-and-fitness/world-cancer-day-india-begins-free-screening-for-oral-breast-and-cervical-cancers/story-1HhWe2qPCpRftX2kgjL5vK.html

  • https://www.indiablooms.com/health-details/H/4261/india-urged-to-bridge-gap-between-evidence-and-policy-in-tackling-women-rsquo-s-cancers.html

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  • Breast Cancer Prediction Using Data Mining Method by Haifeng Wang and Sang Won Yoon, Department of Systems Science and Industrial Engineering State University of New York at Binghamton , Binghamton, NY 13902

  • Amith Bhola and Arvindh Kumar Tiwari, “MACHINE LEARNINGBASED APPROACHES FOR CANCER CLASSIFICATION USING GENE EXPRESSION DATA”, Machine learning and applications: AnInternational Journal, 2(4/4), 01-12. MLAIJ in 2015.

  • Kharya, D. Dubey and Soni,”PRIDICTIVE MACHINE LEARNINGTECHNIQES FOR DETECTING BREAST CANCER”, InternationalJournal of Computer science andInformationTechnologies,Vol,4(6), 2013, 1023-1028.

  • Salama G I, Abdelhalim M and Zeid M A E 2012 Breast Cancer (WDBC)

  • Han J. and Kamber M., Data Mining: Concepts and Techniques, 2nd ed., San Francisco, Morgan Kauffmann Publishers, 2001

  • WBChttps://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+ (Original)

  • WEKA Explorer software tool

  • Somasundaram, Gayathri Devi. "Breast Cancer Prediction System using Feature Selection and Data Mining Methods." International Journal of Advanced Research in Computer Science 2, no. 1 (2011).


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  • Data Mining on Classifiers Prophecy of Breast Cancer Tissues

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Authors

B. G. Deepa
School of CSA, REVA University, India
S. Senthil
School of CSA, REVA University, India
Piyush Singh
School of CSA, REVA University, India

Abstract


The expression "breast cancer" includes to a harmful tumour that has created from cells in the breast. Disease happens because of transformations, or anomalous changes, in the qualities in charge of controlling the development of cells and keeping them solid. The qualities are in every cell's core, which goes about as the "control room" of every cell inside the body.The utilization of machine learning and data mining techniques strategies have transformed the entire procedure of breast cancer growth.

There are a few order calculations like-Naive Bayes, K-Star, Multiclass, Decision Table, Hoeffding Tree. Highlight Selection is the path towards picking a subset of noteworthy highlights (factors, markers) for use in presentation advancement and the part assurance computation. The results show that part decision can improve the precision of classifiers.


Keywords


Breast Cancer, Classifiers, Naïve Bayes, K-Star, Hoeffding Tree, Hybrid classifier.

References