Estimation and Prediction of Crop Yielding Rate Using Machine Learning Techniques

Global warming and uncertainty in climate affects farming directly or indirectly. Estimation and prediction of crop yielding rate helps the farmers to choose the appropriate crop for farming and helps the farmer to take decision on farming and improve their productivity. Machine Learning technology is one of the best and powerful method which helps to estimate and predict the rate of yield of particular crop using set of features. This work aims to predict the yield rate of crop through different Machine Learning algorithms. The prediction helps the farmers to take decision on cultivating the crop. Particularly the authors implemented Support Vector Machine, Multivariate Regression and Random Forest algorithm to build the model and compare the performance metrics and present the comparison results.