Study of Simple K-Means and DBSCAN Clustering Algorithm Using Hypothyroid Dataset

Abhaya Kumar Samal , Subhendu Kumar Pani , Jitendra Pramanik

K-means algorithms, Data mining algorithms, Weka tools, Density based clustering algorithm

In data mining and knowledge discovery, data clustering is considered as one of the major basic research topics that put similar data into groups. A clustering algorithm divides a data set into several groups based on the standard rule of maximizing the intra-class similarity and minimizing the inter-class similarity. In this work, we analyze the performance of K-Means, and Density based clustering. Performance of the 2 techniques are presented and compared using a clustering tool WEKA. These 2 clustering algorithms have applied on hypothyroid dataset which is available at UCI machine learning repository.

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"Study of Simple K-Means and DBSCAN Clustering Algorithm Using Hypothyroid Dataset", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.1, Issue 7, page no.344 - 348, July-2016, Available :https://ijsdr.org/papers/IJSDR1607057.pdf

Volume 1 Issue 7, July-2016

Pages : 344 - 348

Paper Reg. ID: IJSDR_160652

Published Paper Id: IJSDR1607057

Downloads: 000346998

Research Area: Engineering

Country: Bhubaneswar, Odisha, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR1607057

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR1607057

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition