Informatics Publishing Limited

Rohit Miri , Ayush Agrawal , Asha Miri , S. R. Tandan

Abstract

In this era of modern computing world, there are many fuzzy association algorithms is developed and still lots of work have to performed in this area. Some already proposed algorithm reduces data sets or space complexity and some reduces the time complexity and so on. Our proposed algorithms reduce the space complexity by reducing the candidate item sets and large item sets from data sets. We use the row count technique in fuzzy association rules.

Keywords

Candidate Item Sets, Large Item Sets, Time Complexity.

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Prashant Sahu ¹, Jageshwer Shriwas ¹, Rohit Miri ¹, Asha Miri ²

Affiliations
1 Department of Computer Science & Engineering, Dr C V Raman University, Bilaspur Chhttishgarh, IN
2 Department of Computer Science & Engineering, Khairagarh, Chhttishgarh, IN

Abstract

Current era is the age of information, we are living in the era which have flood of information. Sometimes we have very large amount of information which is difficult to handle and sometimes cumbersome to find the exact and required information. To achieve this requirement we use data mining techniques. Classification is the most important part of any data mining technique, which delimits the scope of erroneous and irrelevant information. This survey paper gives an snapshot of the some valuable research work which have be done in the area of classification.

Keywords

Naïve Bayes Classifier, SVM, J48 Algorithm, Data Mining, Association Rule.

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