ABSTRACT
India is popularly known for its best buffalo germplasm throughout the world, being responsible for more than 57% of the world buffalo population. Buffalo is considered as the major dairy animal and backbone of the Indian dairy industry. Neutral network (NN) models are well known for their adaptive capabilities to "learn" relationships among variables. NNs are intelligent techniques for model fitting, which do not depend upon conventional assumptions necessary for traditional regression models. The support vector machines are widely used due to many attractive features and promising empirical performance. Decision Tree (DT) model builds regression models like a tree structure. It splits the data set into smaller and smaller subsets simultaneously leading to the development of an associated DT, incrementally. Linear models are conventional methods of statistics, which were initially developed in the pre-computer era. These intelligent models will provide decision support to organized dairy farms for selecting good buffalo bulls.
