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What is the key idea behind Bayesian classification?
What is the key idea behind Bayesian classification?
- Assuming that the features follow a Gaussian (normal) distribution within each class
- Modeling the probability distribution of word occurrences in each class
- Calculating the probability that a given data instance belongs to each class and then assigning the instance to the class with the highest probability (correct)
- Assuming that features are conditionally independent given the class label
What is the Naive Bayes classifier based on?
What is the Naive Bayes classifier based on?
- Assuming that features are conditionally independent given the class label (correct)
- Calculating the probability that a given data instance belongs to each class and then assigning the instance to the class with the highest probability
- Assuming that the features follow a Gaussian (normal) distribution within each class
- Modeling the probability distribution of word occurrences in each class
In which type of data is Multinomial Naive Bayes classifier used?
In which type of data is Multinomial Naive Bayes classifier used?
- Discrete data (correct)
- Ordinal data
- Continuous data
- Categorical data
What does Gaussian Naive Bayes classifier assume about the features?
What does Gaussian Naive Bayes classifier assume about the features?
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What is the fundamental principle in probability theory that Bayesian classification is based on?
What is the fundamental principle in probability theory that Bayesian classification is based on?
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