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Classification Algorithm in Data Mining


Affiliations
1 School of Computer Science and Applications, REVA University,Bangalore, India
2 School of Computer Science and Applications, REVA University, Bangalore, India
 

Every day, Data generated from business, society, science and engineering, medicine and almost any other aspect of life. By using a large amount of data, we can identify the hidden knowledge by using the data mining process. Data mining consists of anomaly detection, association rule learning, clustering, classification, regression, and summarization. Classification is the main method in data mining and generally used in different field. Classification is a machine learning method used to predict group of data [1]. The main aim of this paper is to study the different classification algorithms in data mining. Classification algorithms are C4.5, ID3, k-nearest neighbor, Naïve Bayes, Support Vector Machine, and Artificial Neural Network. Normally a classification techniques, consists of three approaches Statistical procedure-based learning, Machine Learning and Neural Network.

Keywords

Data Mining, C4.5, ID3, ANN, SVM,, K-Nearest Neighbor, Limitation and Features of the Classification Algorithm.
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  • Classification Algorithm in Data Mining

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Authors

B. V. Sudhakavya
School of Computer Science and Applications, REVA University,Bangalore, India
V. Swathi
School of Computer Science and Applications, REVA University,Bangalore, India
S. Senthil
School of Computer Science and Applications, REVA University, Bangalore, India

Abstract


Every day, Data generated from business, society, science and engineering, medicine and almost any other aspect of life. By using a large amount of data, we can identify the hidden knowledge by using the data mining process. Data mining consists of anomaly detection, association rule learning, clustering, classification, regression, and summarization. Classification is the main method in data mining and generally used in different field. Classification is a machine learning method used to predict group of data [1]. The main aim of this paper is to study the different classification algorithms in data mining. Classification algorithms are C4.5, ID3, k-nearest neighbor, Naïve Bayes, Support Vector Machine, and Artificial Neural Network. Normally a classification techniques, consists of three approaches Statistical procedure-based learning, Machine Learning and Neural Network.

Keywords


Data Mining, C4.5, ID3, ANN, SVM,, K-Nearest Neighbor, Limitation and Features of the Classification Algorithm.

References