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While naive Bayes often fails to produce a good estimate for the correct class probabilities, [16] this may not be a requirement for many applications. For example, the naive Bayes classifier will make the correct MAP decision rule classification so long as the correct class is predicted as more probable than any other class. This is true ...
Bayesian programming [2] is a formal and concrete implementation of this "robot". Bayesian programming may also be seen as an algebraic formalism to specify graphical models such as, for instance, Bayesian networks , dynamic Bayesian networks , Kalman filters or hidden Markov models .
In statistical classification, the Bayes classifier is the classifier having the smallest probability of misclassification of all classifiers using the same set of features. [ 1 ] Definition
naive Bayes classifier and; linear discriminant analysis; discriminative model: logistic regression; In application to classification, one wishes to go from an observation x to a label y (or probability distribution on labels).
C4.5 is an algorithm used to generate a decision tree developed by Ross Quinlan. [1] C4.5 is an extension of Quinlan's earlier ID3 algorithm.The decision trees generated by C4.5 can be used for classification, and for this reason, C4.5 is often referred to as a statistical classifier.
A Bayes filter is an algorithm used in computer science for calculating the probabilities of multiple beliefs to allow a robot to infer its position and orientation. Essentially, Bayes filters allow robots to continuously update their most likely position within a coordinate system, based on the most recently acquired sensor data.
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LDA in Mahout implementation of LDA using MapReduce on the Hadoop platform; Latent Dirichlet Allocation (LDA) Tutorial for the Infer.NET Machine Computing Framework Microsoft Research C# Machine Learning Framework; LDA in Spark: Since version 1.3.0, Apache Spark also features an implementation of LDA; LDA, exampleLDA MATLAB implementation