Study of Various Machine Learning Algorithms Applied to Predict Agricultural Crop Production: A Review Paper

This paper is an effort to review the research study on the use and significance of machine learning techniques in the agriculture crop production domain. Accurate and timely prediction of crop production are essential for policy decisions like pricing, marketing, distribution, import–export, etc. issued by the directorate of economics and statistics. It has to be understood that these estimates are not the objective estimates as these estimate needs lots of eloquent assessment based on many parameters and factors. Machine learning can be used to unite the knowledge of the data with crop yield evaluation for forecasting purpose. This research has been intended to evaluate few techniques like artificial neural networks, Information Fuzzy Network, Decision Tree, Regression Analysis, Bayesian belief network. Time series analysis, Markov chain model.