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Detailed Analysis of Classification Techniques in Data Mining


Volume: 4 Issue: 4
Year of Publication: 2017
Authors: Dr Rashmi Agrawal



Abstract

In classification, no prior information is required for predicting the class label. A classification technique is an organized approach for building classification model from a given input dataset. The learning algorithm of each technique is employed to build a model used to find the relationship between attribute set and class label of the given input data. Various classification techniques used are Decision Tree, Naïve Bayes, and Nearest Neighbour. k- Nearest Neighbour is one of simple and well known classification technique in which distance is measured between input point and all other records of the dataset. The class label of the k-Nearest Neighbour is the class label for input point. The objective of this paper is to understand and analyze various classification techniques used in data mining.

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Keywords

Classification, Decision Tree, Naïve Bayes, Neural Networks, Clustering, Association Rule.




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