Enhancing Seed Selection and Providing Guidance for Cultivation using Random Forest Technique

Abstract

Seed Selection is a very challenging job because for a selection of a seed multifarious parameters are to be taken under consideration. Also seed analysis require a prediction of which seed is suitable which needs a great accuracy as there are numerous things to be taken into account like soil type, ph of soil, nutrient content of soil, elevation of land, weather of the area, etc. Several algorithms have been devised from time to time but each of the methods differs in their own way. The algorithms, which are discussed, are K-Means Algorithm, K-Nearest Neighbor Algorithm, Naïve Bayes Classifier, Decision Tree, Regression Model, etc. Data mining techniques can overcome this challenging job.