Comparing the computational complexity and accuracy of classification algorithms

Authors:
S. Beatrice;R. Thirumahal;S. P. Raja
Affiliations:
Xavier Institute of Engg., Mahim, Mumbai, Maharashtra;TSEC, Bandra, Mumbai, Maharashtra;M.S University, Tirunelveli, Tamil Nadu
Venue:
Proceedings of the International Conference and Workshop on Emerging Trends in Technology
Year:
2010

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SLIQ: A Fast Scalable Classifier for Data Mining

EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Data Mining: Concepts and Techniques

Data Mining: Concepts and Techniques

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Abstract

Decision trees have been widely used for classification in Data mining. Number of decision tree algorithms has been developed in the past. In order to reduce the computational time the On Improving the efficiency of SLIQ (OIESLIQ) algorithm has been developed with an aim to reduce diversity of the decision tree at each split. In order to improve the accuracy, the paper proposes a novel approach (Pioneer classifier algorithm) to embark upon the other two algorithms.