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Prediction of customer behaviour analysis using classification algorithms
Customer Relationship management plays a crucial role in analyzing of customer behavior patterns and their values with an enterprise. Analyzing of customer data can be efficient performed using various data mining techniques, with the goal of developing business strategies and to enhance the busines...
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Main Authors: | , |
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Format: | Conference Proceeding |
Language: | English |
Online Access: | Get full text |
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Summary: | Customer Relationship management plays a crucial role in analyzing of customer behavior patterns and their values with an enterprise. Analyzing of customer data can be efficient performed using various data mining techniques, with the goal of developing business strategies and to enhance the business. In this paper, three classification models (NB, J48, and MLPNN) are studied and evaluated for our experimental purpose. The performance measures of the three classifications are compared using three different parameters (accuracy, sensitivity, specificity) and experimental results expose J48 algorithm has better accuracy with compare to NB and MLPNN algorithm. |
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ISSN: | 0094-243X 1551-7616 |
DOI: | 10.1063/1.5032060 |