Comparative Analysis of SVM, Decision Tree, Random Forest for Crop Recommendation

Abstract

A sizable portion of Indians view agriculture as their primary source of income. The cultivation of crops is crucial to the economy. Crop production of poor quality is frequently the result of choosing the incorrect crops for the wrong soil or not knowing enough about the growth potential of various crops. The suggested method, which bases crop suggestion on machine learning, is based on measurements of soil properties that have been previously recorded This method helps to maintain crop health and reduces the likelihood of soil degradation. Numerous elements, among them rainfall. Temperature, pH, N, P, K, and humidity are all analyzed using machine learning techniques including random forests, decision trees, and support vector machines. Based on these analyses, recommendations are provided for cultivating an appropriate crop.