Crop Yield Analysis Using Combinatorial Multivariate Linear Regression

India being a horticultural nation, its economy prevalently relies on agribusiness yield development and associated agro-industry items. In India, farming is, to a great extent, affected by water, which is profoundly eccentric. Farming development relies on differing soil parameters, specifically Nitrogen, Phosphorus, Potassium, Soil dampness, Surface temperature, and climate perspectives, which incorporate temperature, rainfall, and many more. India currently is quickly advancing towards specialized improvement. A few methods and approaches of foreseeing and showing crop yields have been grown before with the changing pace of achievement. The proposed model will coordinate the information obtained from Indian Meteorological Department (IMD), Directorate of Economics and Statistics (DES), by applying machine learning techniques: Combinatorial Multivariate Linear Regression(C-MLR), the proposed model, can give the actual accuracy of predicted crop yield