Application of k-NN and Naive Bayes Algorithm in Banking and Insurance Domain
In todays globalized world, Business Intelligence software would form part of many firms business oriented information technology strategies. Before such strategy could be planned, these firms would require in-depth data analysis on the products that they would be planning to sell such as sales purchases, staff costs and other items that could potentially impact services or goods. We have applied data mining classification technique in Banking and Insurance domain to provide solution and prediction model. In classification machine learning technique, we will use k-NN and Naive Bayes algorithm on Portuguese bank dataset and Dutch insurance company dataset and shall also compare accuracy of their classification.
Keywords: Data Mining, k-Nearest Neighbor, Naive Bayes and Classification Algorithm
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ABOUT THE AUTHORS
Gourav Rahangdale
Pursued Engineering with Master Degree, Dual Degree Integrated PG Program, Department of Computer Science & Engineering, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India
Manish Ahirwar
Assistant Professor, Department of Computer Science & Engineering, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India
Mahesh Motwani
Associate Professor, Department of Computer Science & Engineering, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India
Gourav Rahangdale
Pursued Engineering with Master Degree, Dual Degree Integrated PG Program, Department of Computer Science & Engineering, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India
Manish Ahirwar
Assistant Professor, Department of Computer Science & Engineering, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India
Mahesh Motwani
Associate Professor, Department of Computer Science & Engineering, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India