comparison of two machine learning algorithms for efficiency

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Naive Bayes classifier works on the assumption that all variables are independent of each other and the probability of a variable being true or false depends only on its own value. In other words, it assumes that all variables are conditionally independent given their values (or observed frequencies). The dependent variable in this case is called as latent variable

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