Pattern Classification by Richard Duda, Peter Hart, and David Stork renders the principal algorithms of pattern classification with the help of low range MATLAB objects. The building of objects is illustrated in a systematic manner using visualizations and data building algorithms with the help of solved programs. The design of algorithm has been explained in a series of chapters with the initial chapters on Bayesian concepts like Bayesian Decision Theory and Parameter Estimation along with the concept of Maximum-Likelihood.
