A Comparative Study of Data Mining Classification Techniques using Lung Cancer Data

International Journal of Computer Trends and Technology (IJCTT)          
© 2015 by IJCTT Journal
Volume-22 Number-2
Year of Publication : 2015
Authors : Er.Tapas Ranjan Baitharu, Dr.Subhendu Kumar Pani


Er.Tapas Ranjan Baitharu, Dr.Subhendu Kumar Pani "A Comparative Study of Data Mining Classification Techniques using Lung Cancer Data". International Journal of Computer Trends and Technology (IJCTT) V22(2):91-95, April 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Now-a-days the most important cause of death for both men and women is the cancer Lung Cancer is a disease of uncontrolled cell growth in tissues of the lung. Detection of Lung Cancer in its early stage is the key of its cure. Data classification is an important task in KDD (knowledge discovery in databases) process. It has several potential applications. The performance of classifiers is strongly dependent on the data set used for learning. It leads to better performance of the classification models in terms of their predictive or descriptive accuracy, diminishing of computing time needed to build models as they learn faster, and better understanding of the models. In this paper, a comparative analysis of data classification accuracy using lung cancer data in different scenarios is presented. The predictive performances of popular classifiers are compared quantitatively.

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Classification, Data Mining, Lung Cancer, Naive Bayes.