Parallel K-Means Algorithm on Agricultural Databases
A cluster is a collection of data objects that are similar to each other and dissimilar to the data objects in other clusters. K-means algorithm has been used in many clustering work because of the ease of the algorithm. But time complexity of algorithm remains expensive when it applied on large datasets. To improve the time complexity, we implemented parallel k-means algorithm for cluster large dataset. For our study we take agricultural datasets because of limited researches are done in agricultural field
Keywords: Clustering,k-means,parallel k-means, agriculture
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ABOUT THE AUTHORS
V.Ramesh
KANCHIPURAM, INDIA
K.Ramar
Principal, Einstein College of Engineering, Tirunelveli, India
S.Babu
KANCHIPURAM, INDIA
V.Ramesh
KANCHIPURAM, INDIA
K.Ramar
Principal, Einstein College of Engineering, Tirunelveli, India
S.Babu
KANCHIPURAM, INDIA
