Crop Yield Prediction based on Indian Agriculture using Machine Learning
Potnuru Sai Nishant, Pinapa Sai Venkat, B. Avinash, Bhukya Jabber
Abstract
In India, we all know that Agriculture is the backbone of the country. This paper predicts the yield of almost all kinds of crops that are planted in India. This script makes novel by the usage of simple parameters like State, district, season, area and the user can predict the yield of the crop in which year he or she wants to. The paper uses advanced regression techniques like Kernel Ridge, Lasso and ENet algorithms to predict the yield and uses the concept of Stacking Regression for enhancing the algorithms to give a better prediction.
Topics & Concepts
Lasso (programming language)Yield (engineering)AgricultureRidgeKernel (algebra)Crop yieldMachine learningRegressionComputer scienceArtificial intelligenceAgricultural engineeringCropMathematicsStatisticsAgronomyGeographyEngineeringForestryBiologyMetallurgyWorld Wide WebArchaeologyCartographyMaterials scienceCombinatoricsSmart Agriculture and AIAgricultural Economics and PracticesSpectroscopy and Chemometric Analyses