Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Performance Analysis of Bayes Classification Algorithms in WEKA Tool using Bank Marketing Dataset

Author : M. Purnachary 1 B. Srinivasa S P Kumar 2 Humera Shaziya 3

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.

Reference :

    1. Pang-Ning Tan, Vipin Kumar- Introduction to Data Mining (Second Edition) Pearson International Edition.
    2. Jiawei Han University of Illinois at Urbana– Champaign Micheline Kamber -Data Mining Concepts and Techniques Third Edition, Elsevier.
    3. UCI Machine Learning Repository https:// archive. ics. uci. Edu /ml /datasets /bank +marketing
    4. Marina Sokolova- A systematic analysis of performance measures for classification tasks, Information Processing and Management 45 (2009) 427–437 Elseviers https://www.sciencedirect.com/science/article/pii/S0306457 309000259

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