Naive Bayes Continuous is a supervised learning component. It implements the naive bayes principle for continuous predictors (gaussian assumption, heteroscedasticity or homoscedasticity). The main originality is that it provides an explicit model corresponding to a linear combination of predictors and, eventually, their square.
Enhancement of the reporting module.
Tuesday, October 19, 2010
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