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Naive Bayes Algorithm with Implementation
Naive Bayes Algorithm with Implementation Quiz
Question 1
What is the primary assumption of the Naive Bayes algorithm?
All features are dependent on each other
All features are independent of each other
All features have equal weight
All features have the same mean
Question 2
Which probability principle does Naive Bayes follow?
Bayes Theorem
Maximum Likelihood
Gradient Descent
Regression Analysis
Question 3
Which Naive Bayes variant is suitable for text classification problems?
Gaussian Naive Bayes
Bernoulli Naive Bayes
Multinomial Naive Bayes
Logistic Regression
Question 4
How are continuous features assumed to be distributed in Naive Bayes?
Uniformly
Binomially
Normally
Exponentially
Question 5
What is the role of the encode_class function?
Convert class labels into numeric values
Normalize features
Split dataset into training and testing
Calculate Gaussian probability
Question 6
Which probability distribution is used for continuous features in this Naive Bayes implementation?
Multinomial distribution
Bernoulli distribution
Gaussian distribution
Poisson distribution
There are 6 questions to complete.
