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
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
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