Published Paper Details:

In general, agriculture is the backbone of India and also plays an important role in Indian economy. Most of Indians have agriculture as their occupation. Farmers usually have the mind-set of planting the same crop, using more fertilizers and following the public choice. But now-a-days, food production and prediction is getting depleted due to unnatural climatic changes, which will adversely affect the economy of farmers by getting a poor yield and also help the farmers to remain less familiar in getting high yield of crops. Machine learning is one such advanced technique deployed to predict crop yield in agriculture. By looking at the past few years, there have been significant developments in how machine learning can be used in various industries and research. The surveyed research papers have given a rough idea about using ML with only one attribute. It gives us an idea for the finest predicted crop which will be cultivate in the field weather conditions [1]. These predictions can be done by a machine learning algorithm called Random Forest. Various machine learning techniques we are using such as KNN, DT, RF, BAGGING and GRADIENT BOOSTING [7]. However, the selection of the appropriate algorithm from the pool of available algorithms imposes challenge to the researchers with respect to the chosen crop. This system will be useful to justify which crop can be grown in a particular region [8].