Soybean Productivity Modelling using Decision Tree Algorithms

Abstract

Data mining applications in agriculture is a relatively new approach for forecasting / predicting of agricultural crop/animal management. In the present study an attempt has been made to study the influence of climatic parameters on soybean productivity using decision tree induction technique. The findings of Decision tree were framed into different rules for better understanding by the end users. The study findings will help the researchers, policy makers and farmers in predicting/forecasting the crop yield in advance for market dynamics.