It is a classification technique based on Bayes’ theorem with an assumption of independence between predictors. A Naive Bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature. Naive Bayesian model is easy to build and particularly useful for very large data sets.… Continue reading Implementing the Naive-Bayes Machine learning Model
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Naive Bayes Algorithm in Python
Bayes’ Theorem provides a way that we can calculate the probability of a piece of data belonging to a given class. Bayes’ Theorem is stated as: P(class|data) = (P(data|class) * P(class)) / P(data) Where P(class|data) is the probability of class given the provided data. Naive Bayes is a classification algorithm for binary (two-class) and multiclass… Continue reading Naive Bayes Algorithm in Python