Exploring Regression Techniques for Predictions of Wheat and Rice Prices in India
Journal Title: International Research Journal of Computer Science - Year 2016, Vol 0, Issue 0
Abstract
Agriculture products play an important role in the economy of the country. In India, Wheat and Rice are the two major agriculture products and lots of economical decisions are taken by considering the prices of these agriculture products. Regression techniques are the most commonly and popularly used techniques in prediction. In this paper three regression techniques namely, Linear, Logistic and Isotonic regression are used for carrying experimental study on predicting Wheat and Rice prices for Indian markets. Performance parameters Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Relative Absolute Error (RAE), and Root Relative Squared Error (RRSE) are calculated for comparing the regression techniques for prediction of Rice and Wheat prices.
Authors and Affiliations
Naresh Kumar Nagwani, Kesari Verma, Shrish Verma
Keywords
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