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Questions and Answers
What is the main purpose of a Naive Bayes Classifier?
What is the main purpose of a Naive Bayes Classifier?
- To identify a model that best fits the relationship between variables
- To predict the class label of unknown records (correct)
- To draw the decision boundary in the feature space
- To calculate the Bayes Error Rate accurately
In a Naive Bayes Classifier, how is the relationship between variables X and class variable Y defined?
In a Naive Bayes Classifier, how is the relationship between variables X and class variable Y defined?
- $P(Y|X)$: The conditional probability/posterior probability for Y (correct)
- $P(X|Y)$: The likelihood of Y given X
- $P(X)$: The prior probability of X
- $P(Y)$: The posterior probability of Y
What is the purpose of Laplacian correction in a Naive Bayes Classifier?
What is the purpose of Laplacian correction in a Naive Bayes Classifier?
- To increase the prior probabilities for all classes
- To reduce the Bayes Error Rate significantly
- To adjust probabilities to avoid zero-probability issues (correct)
- To draw the decision boundary more accurately
Which theorem is used for combining prior knowledge of classes with new evidence in a Naive Bayes Classifier?
Which theorem is used for combining prior knowledge of classes with new evidence in a Naive Bayes Classifier?
What does the Bayes Error Rate represent in classification models?
What does the Bayes Error Rate represent in classification models?
How does a Bayesian Classifier example differ from a non-Bayesian classifier?
How does a Bayesian Classifier example differ from a non-Bayesian classifier?
What is the objective of a Bayesian classifier?
What is the objective of a Bayesian classifier?
Why is the Naive Bayes Classifier considered 'naive'?
Why is the Naive Bayes Classifier considered 'naive'?
What does a Bayesian Classifier predict?
What does a Bayesian Classifier predict?
In a Naive Bayes Classifier, how is the most likely class determined?
In a Naive Bayes Classifier, how is the most likely class determined?
Which assumption does the Naive Bayes Classifier make regarding variable effects?
Which assumption does the Naive Bayes Classifier make regarding variable effects?
In the Bayesian Classifier example provided, if Team B hosts the next match, which team is most likely to win?
In the Bayesian Classifier example provided, if Team B hosts the next match, which team is most likely to win?
What property of the naive Bayesian classifier makes computation of P(X|Ci) less expensive?
What property of the naive Bayesian classifier makes computation of P(X|Ci) less expensive?
Which technique in naive Bayesian classifiers can help handle the issue of class-conditional probability becoming zero?
Which technique in naive Bayesian classifiers can help handle the issue of class-conditional probability becoming zero?
What is Laplacian correction in the context of probability estimation?
What is Laplacian correction in the context of probability estimation?
Why does naive Bayesian classifier provide a theoretical justification for other non-Bayesian classifiers?
Why does naive Bayesian classifier provide a theoretical justification for other non-Bayesian classifiers?
How do correlated variables affect the performance of naive Bayes classifiers?
How do correlated variables affect the performance of naive Bayes classifiers?
In a Bayesian classifier example, when 'Marital status=Married' is never associated with 'Defaulted borrower class=Yes', what issue does this represent?
In a Bayesian classifier example, when 'Marital status=Married' is never associated with 'Defaulted borrower class=Yes', what issue does this represent?
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