A REVIEW ON CROP YIELD PREDICTION USING RANDOM FOREST, SVM & KNN

Abstract

Nowadays we all see machine Learning is famous for data prediction we use Supervised learning techniques & Unsupervised learning techniques. By using this prediction, industries, organizations are improving their performance, productivity & income rate. For supervised learning, we can use algorithms like Random Forests, Support Vector Machines, decision trees & Linear classifiers are used in classification. Linear regression & Logistic regression are used for regression. In unsupervised learning we can use clustering, data mining, etc. in our paper we will collect data on the crop for Maharashtra State for Rabbi & Kharif Season. According to this data set we will apply a supervised technique on it for crop prediction. By using this result farmer can take decision & improve their income rate. Also, we will provide the recent market price of crops to farmers when they use our system for prediction.