Agriculture Commodity Price Forecasting using Ml Techniques

Abstract

India is mainly an agricultural country the farmer is an important part of agriculture. Agriculture mainly depends on him. Even then the farmers cannot predict prices for their commodities because prediction of prices plays a major challenge. Several characteristics are taken into account so that the crop price forecast is accurate. We consider the attributes of the Mysore region to make it a real-time application framework. Price prediction is a big issue for farmers who are not aware of the market prices. Forecasting price of agriculture commodities helps the agriculturist and also the agriculture department of mysore region to make decisions. The new model predicts the accuracy for the agricultural yields and it also avoids the role of middle man.