Parametric vs Non - Parametric Generative Models
نویسندگان
چکیده
The contrast is exemplified by the following classification task. Let’s assume that we are given data, X , i.e. the observed variable and we want to determine its class label, Y, the unobserved (target) variable. A generative classifier, such as Naive Bayes, makes use of the joint distribution of X and Y, i.e. P(X ,Y) to perform this inference. While a discriminative classifier, such as a Logistic Regression, would directly model the posterior class probabilities, i.e. P(Y|X ) to perform this inference.
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