Performance Analysis of K-Means and K-Medoid Clustering Algorithms Using Agriculture Dataset

Journal of Emerging Technologies and Innovative Research (JETIR), January 2019, Volume 6, Issue 1

7 Pages Posted: 26 Mar 2019

See all articles by P. Surya

P. Surya

Periyar University

I Laurence Aroquiaraj

Periyar University - Department of Computer Science

Date Written: March 3, 2019

Abstract

Agriculture is backbone of India. Data mining is a technique to extract the knowledge from the huge amount of datasets. Clustering is used to classify the similar group of objects in the unknown dataset. Here, in this paper clustering techniques was implemented for the analysis of Agriculture dataset. The proposed is to apply the clustering techniques for classify the Agriculture dataset using Kmeans and Kmedoid (PAM). So as to classify the agriculture dataset and also a performance analysis was done between these Kmeans and Kmedoid (PAM) techniques depend on the performance metrics.

Keywords: Clustering, Agriculture, Kmeans, Kmedoid

Suggested Citation

Surya, P. and Laurence Aroquiaraj, I, Performance Analysis of K-Means and K-Medoid Clustering Algorithms Using Agriculture Dataset (March 3, 2019). Journal of Emerging Technologies and Innovative Research (JETIR), January 2019, Volume 6, Issue 1, Available at SSRN: https://ssrn.com/abstract=3345800

P. Surya (Contact Author)

Periyar University

Periyar Palkalai Nagar
Salem, Tamil Nadu 636011
India

I Laurence Aroquiaraj

Periyar University - Department of Computer Science ( email )

Periyar Palkalai Nagar
Salem, Tamil Nadu 636011
India

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