APPLICATION OF BAYESIAN APPROACH TO DECISION TREE ALGORITHM FOR CLASSIFICATION OF SOIL TYPES

This paper details the application of a decision tree algorithm for classification of soil types. The productivity of agriculture depends on environmental conditions and soil types. Soil dataset of particular area is downloaded from the Kaggle website for the purpose of finding the classification of soil types and based on the types of soil predicted the agriculturist will sow the seed. In this paper Soil types are classified by applying Bayesian approach to Decision Tree algorithm with Bayesian model is used for finding the classification of soil types. The idea behind is rather simple but powerful. The proposed algorithm offers some unique features not to be found in any other tree inducers while at the same time it can produce better results for many difficult problems. Experimental results are presented which illustrate the performance of generating best decision tree for classifying soil type from the given soil dataset. The Algorithm of Bayesian approach to Decision Tree helps to classify the soil types more accurately than the existing Algorithms KNN, SVM and Decision Tree selected for this research paper