Abstract

In India, Agriculture plays a pivotal role in the Indian economy, contributing approximately 17% to the total GDP and employing over 60% of the population. Not only in India, agriculture sector is one of the most important sectors in all over the world. In the past few years many machine learning algorithms are being used to recommend the best crop for farmers under the different conditions. It is important to recommend the best crop to the farmers not only for the better growth but also for the decrease the risk of farmers. Tn this paper we are doing the review of different machine learning algorithms like Logistic Regression, Naïve Bayes, Support Vector Machine, Extra Trees, Decision Tree, Randam Forest and many more. And then we find out the best algorithms based on their accuracy rate and used that algorithm in our project to recommend the crop. It also requires the dataset to train our system. So, we take the dataset of values like N, P, K, temperature, humidity, ph, and rainfall.