What does the Bayes' theorem of classification provide a framework for? Evaluating the accuracy of linear models Estimating the coefficients in logistic regression Making predictions based on prior knowledge and evidence Testing the significance of predictors in linear regression

What is the fundamental concept behind Bayes' Theorem? a. It determines the likelihood of observing rare events in a dataset. b. It estimates the conditional probability of an event given prior knowledge. c. It updates the probability of a hypothesis based on new evidence. d. It calculates the joint probability of two events occurring together.

What is a logistic regression algorithm?Question 8Answera.A model used for classification tasks by predicting the probability of an event occurringb.A clustering algorithm used in unsupervised learningc.A linear model used to make predictions in supervised learningd.A tree-like model used to make predictions in supervised learning

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

How does the Naive Bayes classifier calculate the probability of a data point belonging to a particular class?Select one:a.By using the maximum likelihood estimationb.By using the least squares methodc.By using the gradient descent algorithmd.By using the Bayes theorem

How does the Naive Bayes classifier calculate the probability of a data point belonging to a particular class?Select one:a.By using the least squares methodb.By using the gradient descent algorithmc.By using the maximum likelihood estimationd.By using the Bayes theorem