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Naive Bayes Classifier
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Naive Bayes Classifier

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Questions and Answers

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

  • Linear regression
  • Gaussian distribution
  • Bayes' theorem (correct)
  • Principal component analysis

    • 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

    <p>Kernel density estimation</p> Signup and view all the answers

    Naive Bayes classifiers are highly scalable and require a number of parameters linear in the number of

    <p>Variables (features/predictors)</p> Signup and view all the answers

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