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Classification, Clustering and Regression in Agricultural Data Mining


Affiliations
1 Department of Computer Engineering, Punjabi University, Patiala, India
2 Punjabi University, Patiala, India
 

Agricultural Data Mining is relatively novel field for research as compared to that of Educational data mining, Medical data mining, Business data mining etc. However, it is attracting many researchers for contributing to this area. This Paper provides an overview on the Data Mining Techniques which are frequently used in Agricultural Data Mining and some of their applications. These techniques will include Classification, Clustering and Regression to be naming a few. Knearest, Kmeans and Multiple Linear Regression Algorithms are discussed with their use in applications like predicting crop yield, olive production and others. Focus of this paper is to introduce the readers with a wide range of possibilities for research in the Agriculture.
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  • Classification, Clustering and Regression in Agricultural Data Mining

Abstract Views: 106  |  PDF Views: 6

Authors

Gurpinder Singh
Department of Computer Engineering, Punjabi University, Patiala, India
Kanwal Preet Singh Atwal
Punjabi University, Patiala, India

Abstract


Agricultural Data Mining is relatively novel field for research as compared to that of Educational data mining, Medical data mining, Business data mining etc. However, it is attracting many researchers for contributing to this area. This Paper provides an overview on the Data Mining Techniques which are frequently used in Agricultural Data Mining and some of their applications. These techniques will include Classification, Clustering and Regression to be naming a few. Knearest, Kmeans and Multiple Linear Regression Algorithms are discussed with their use in applications like predicting crop yield, olive production and others. Focus of this paper is to introduce the readers with a wide range of possibilities for research in the Agriculture.