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ComplementNaiveBayesModel's ModelParameter: is a k-list of vectors $\theta_c$, c=1 to k (number of classes), where $\theta_{ci}$ is the probability of word/feature i NOT in class c, with i = 1 to p (number of words/boolean features). We can therefore represent this model parameter as a k x p matrix whose rows are classes and columns are words/boolean features. We call this a ComplementCCProbMatrix.

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  • ComplementNaiveBayesModel's ModelParameter: is a k-list of vectors $\theta_c$, c=1 to k (number of classes), where $\theta_{ci}$ is the probability of word/feature i NOT in class c, with i = 1 to p (number of words/boolean features). We can therefore represent this model parameter as a k x p matrix whose rows are classes and columns are words/boolean features. We call this a ComplementCCProbMatrix.
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