Crop Recommendation System using ML

Abstract

The crop recommendation system using machine learning is an intelligent decision support system that provides recommendations to farmers on the most suitable crop to cultivate based on soil and weather conditions like temperature, humidity, rainfall, nitrogen, potassium, phosphorus and pH value of the soil. This system uses machine learning algorithms like Decision Tree, Random Forest, Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to analyse data on soil properties, climate, and other relevant factors to generate personalized crop recommendations for each farmer. Keywords: Crop Recommendation, temperature, humidity, rainfall, nitrogen, potassium, phosphorus, ph value, Decision Tree, Random Forest, Naïve Bayes, Support Vector Machine (SVM), Logistic Regression, machine Learning.