The matlab code implements the ensemble of DECISION tree classifiers proposed in: "L. Nanni and A. Lumini, Input Decimated Ensemble based on Neighborhood Preserving Embedding for spectrogram classification, Expert Systems With Applications doi:10.1016/j.eswa.2009.02.072 "
The algorithm ID3 (Quinlan) uses the method top-down induction of DECISION trees. Given a set of classified examples a DECISION tree is induced, biased by the information gain measure, which heuristically leads to small trees. The examples are given in attribute-value representation. The set of possible classes is finite. Only tests, that split the set of instances of the underlying example languages depending on the value of a single attribute are supported.
PhD research, you have already
made a DECISION that will have a major impact on the success of your
project, and perhaps even on your future career. You have chosen to
work in a particular research group, under the guidance of a particular
thesis advisor or supervisor.
Before you even get started on your PhD research, you have already
made a DECISION that will have a major impact on the success of your
project, and perhaps even on your future career. You have chosen to
work in a particular research group, under the guidance of a particular
thesis advisor or supervisor.
One of the most important issues affecting
the implementation of microcontroller
software deals with the data-DECISION
algorithm. Data-DECISION refers to decoding
the DIO-pin from the CC400/CC900. Two
main principles exist for decoding
Manchester-coded data: Data DECISION
based on timing the period between
transitions, and data DECISION based on
oversampling.
bayeserr - Computes the Bayesian risk for optimal classifier.
％ bayescln - Classifier based on Bayes DECISION rule for Gaussians.
％ bayesnd - Discrim. function, dichotomy, max aposteriori probability.
％ bhattach - Bhattacharya s upper limit of mean class. error.
％ pbayescln - Plots discriminat function of Bayes classifier.
