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

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

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Year of publication:	2019
Authors:	Surya, P. ; Laurence Aroquiaraj, I
Publisher:	[S.l.] : SSRN
Subject:	Clusteranalyse \| Cluster analysis \| Algorithmus \| Algorithm \| Landwirtschaft \| Agriculture \| Regionales Cluster \| Regional cluster \| Performance-Messung \| Performance measurement