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Naive Bayes classifiers are a type of
Naive Bayes classifiers are a type of
- Supervised learning algorithm (correct)
- Unsupervised learning algorithm
- Deep learning algorithm
- Reinforcement learning algorithm
Naive Bayes classifiers are based on
Naive Bayes classifiers are based on
- Linear regression
- Gaussian distribution
- Bayes' theorem (correct)
- Principal component analysis
Naive Bayes classifiers make the assumption of
Naive Bayes classifiers make the assumption of
- Only linear relationship between features
- Strong dependence between features
- No relationship between features
- Strong independence between features (correct)
Naive Bayes classifiers can achieve high accuracy levels when coupled with
Naive Bayes classifiers can achieve high accuracy levels when coupled with
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Naive Bayes classifiers are highly scalable and require a number of parameters linear in the number of
Naive Bayes classifiers are highly scalable and require a number of parameters linear in the number of
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