Naive Bayes classifier is a type of supervised learning - True or False?Answer choicesSelect an optionTRUEFALSEUnsupervised learningNone of the options

Which of these is a supervised learning algorithm?Answer choicesSelect an optionClassificationClusteringPCANone o

Which of the following statements about Naive Bayes classification is true?It assumes that all features are independent of each other.It works well only with numerical data.It is a type of unsupervised learning algorithm.It is primarily used for regression tasks.

What is the main assumption of the Naive Bayes classifier?Answer areaThe attributes are highly dependentThe attributes are equally importantThe attributes are conditionally independent given the classThe attributes are unimportant for classification

he Naïve Bayes classifier assumes that (Select ANY correct answer)A.the attributes individually follow a Gaussian conditional probability distribution, given the class.B.the attributes individually follow a Gaussian probability distribution, independent of the class.C.the value of any attribute is statistically independent of the value of any other attribute (given the class value).D.the value of any attribute is statistically dependent of the value of any other attribute (given the class value).

What is the Naive Bayes classifier used for?Select one:a.To classify data into different categories based on certain featuresb.To predict the value of a continuous variablec.All of the aboved.To predict the probability of an event occurring