A Survey on Various Data Mining Techniques in Field of Agriculture for Prediction of Crop Yield

Huma Khan ^[4] | Shahista Navaz ^[2] | Dr. S. M. Ghosh ^[2]

Abstract: Agriculture is a key to the economy and infrastructure of India. It plays the significant most strategic role in the progress and financial growth of the nation. In Order to get a proper tab on the agriculture sector of the nation, state wise and geography wise, an appropriate program can be deployed, with the help of this program we can predict the best crop. Crop yield prediction provides information for decision makers to maximize the crop productivity. Data mining technology proved to be a better choice for this purpose and has become an interesting and recent research topic in agriculture to predict the crop yield. This paper presents a brief comparative study of various methods and techniques available that can be used to predict the crop yield in data mining.

Keywords: K-Means, K-Nearest Neighbor KNN, Support Vector Machine SVM, Multiple Linear Regression MLR

Edition: Volume 6 Issue 5, May 2017,

Pages: 631 - 633