The document centre seems only explain how to use these functions, but just in an very brief way. I know Mathmatica is not open source, so we can not expect to see the code of the function, but are there any materials that describe the internal algorithm in more detailed informations? Like how does Mathematica decide to use a logistic model or a Markov model to do the classify or prediction.
If you want to have a description of the method used by a given
ClassifierFunction you can do:
Also, the methods used are quite classic, so you can easily find documentation on the web.
If you want to know why Classify uses a given model there is a simple answer: Classify tries to find the model that has the highest likelihood on unseen data (that is on test sets). In a nutshell, Classify first selects possible candidates (from heuristics, depending on the characteristics of data). Then the models compete against each other using cross validation techniques, and the best model is selected. There are subtleties in the automation though (not every model get all the data for speed reason etc.), and we intend to make it smarter in the future, which is the reason we did not give a precise description in the documentation.