Machine Learning

  Bayes Theorem, Naive Bayes Algorithm, KNN Algorithm MCQs 1.      Formula for Bayes theorem is _______ Ans: A 2.      The bayesian network can be used to answer any query by using:- (A) Full distribution (B) Joint distribution (C) Partial distribution (D) All of the above Ans: B 3.        Which of the following is correct about the Naive Bayes? (A) Assumes that all the features in a dataset are independent (B) Assumes that all the features in a dataset are equally important (C) Both (D) None of the above Ans: C 4.        Naïve Bayes Algorithm is a ________ learning algorithm. (A) Supervised (B) Reinforcement (C) Unsupervised (D) None of these Ans: A   5.      Examples of Naïve Bayes Algorithm is/are (A) Spam filtration (B) Sentimental analysis (C) Classifying articles (D) All of the above Ans: D 6.        Naïve Bayes algorithm is based on _______ and used for solving classification problems. (A) Bayes Theorem (B) Candidate elimination algorithm