Main Article Content
In recent years, huge amount of data is stored in database which is increasing at a tremendous speed. This requires need for some new techniques and tools to intelligently analyze large data sets to acquire useful information. This growing need demands for a new research field called Knowledge Discovery in Databases (KDD) or Data Mining. The main objective of the data mining process is to extract information from a large data set and transform it into some meaningful form for further use. Classification is the one of data mining techniques which is used to classify categorical data item in a set of data into one of predefined set of classes or groups, In this paper, the goal is to provide a comprehensive analysis of different classification techniques in data mining that includes decision tree, Bayesian networks, k-nearest neighbor classifier & artificial neural network.
How to Cite
, S. P. S. K. “A Comparative Analysis of Classification Techniques on Categorical Data in Data Mining”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 3, no. 8, Aug. 2015, pp. 5142-7, doi:10.17762/ijritcc.v3i8.4806.