CROP YIELD PREDICTION USING MACHINE LEARNING

Abstract

Agriculture is one of the major and the least paid occupation in India. Machine learning
can bring a boom in the agriculture field by changing the income scenario through growing the
optimum crop. This paper focuses on predicting the yield of the crop by applying various
machine learning techniques. The outcome of these techniques is compared on the basis of mean
absolute error. The prediction made by machine learning algorithms will help the farmers to
decide which crop to grow to get the maximum yield by considering factors like temperature,
rainfall, area, etc. The classifier models used here include Logistic Regression, Naive Bayes and
Random Forest, out of which the Random Forest provides maximum accuracy. The prediction
made by machine learning algorithms will help the farmers to come to a decision which crop to
grow to induce the most yield by considering factors like temperature, rainfall, area, etc. This
bridges the gap between technology and agriculture sector.