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Investigation of Performance Analysis of Classification Algorithm in Data Mining


Dr. Mohd Ashraf, Dr. Zair Hussain
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Data mining is now one of the most active field of research. Extracting those nuggets of information is becoming crucial and one of its important technique is classification. It helps to group the data in some predefined classes. Various techniques for classification exists which classifies the data using different algorithms. Each algorithm has its own area of best and worst performance. This paper concentrates on the four most famous algorithms, i.e., Decision Tree, Na´ve Bayes, K Nearest Neighbour and Genetic Programming and the effect on their performance of time and accuracy when the number of instances are incrementally decreased. This paper will also investigate the difference in result when working with binary class or multiclass datasets and suggest the algorithms to follow when using certain kind of dataset.

Dr. Mohd Ashraf, Dr. Zair Hussain

Decision Tree, Na´ve Bayes, K-Nearest Neighbor, Genetic Programming, Accuracy

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Publication Details

Published in : Volume 4 | Issue 4 | March-April - 2018
Date of Publication Print ISSN Online ISSN
2018-04-30 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
58-66 IJSRSET184425   Technoscience Academy

Cite This Article

Dr. Mohd Ashraf, Dr. Zair Hussain, "Investigation of Performance Analysis of Classification Algorithm in Data Mining", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 4, pp.58-66, March-April-2018.
URL : http://ijsrset.com/IJSRSET184425.php