The Performance Analysis and comparison of Machine Learning Classifiers and Neural Network on Crop Recommendation

Agriculture sector is the backbone of the Indian Economy. In India, few farmers are still using some ancient farming methods. e.g. Slash-and-Burn, Crop rotation. Without the knowledge of soil fertility crops cultivation is chosen randomly, which causes the yield of the crops may degrade. For suitable crop cultivation, the parameters like rainfall, soil contents and weather parameters are the most considerable factors. The fertilizers like Nitrogen (N), Phosphorous (P) and Potassium (K) are the most required fertilizers for any crop. In this paper, A Neural Network is designed and a crop recommendation dataset, which is downloaded from Kaggle and trained on it and also compared with the other Machine learning models.