Author : M. Purnachary 1
Date of Publication :23rd February 2018
Abstract: Data Mining is an interdisciplinary field that aims to extract knowledge or insights from data in various forms, either structured or unstructured. Classification is a supervised learning approach of data mining and It is used to classify huge data. WEKA is powerful machine learning tool that contains many inbuilt algorithms to extract knowledge. In this paper we tried to analyze the performance of two built in Bayes type of Classification algorithms (Bayes Net, Naïve Bayes) in WEKA tool using Bank Marketing Dataset which is extracted from UCI Repository. It has been observed that Bayes Net classification algorithm performed better compared to Naïve Bayes algorithm.
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