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GlossaryMachine LearningNaive Bayes Classifier

Naive Bayes Classifier

[naɪˈiv beɪz ˈklæsəˌfaɪər]
Machine Learning
Last updated: December 9, 2024

Definition

A probabilistic model assuming feature independence.

Detailed Explanation

The Naive Bayes Classifier applies Bayes’ theorem with the assumption that features are independent given the class label. It’s efficient for large datasets and performs well despite its simplicity.

Use Cases

Spam filtering text classification sentiment analysis medical diagnosis recommendation systems.

Related Terms

Data Drift

Changes in the distribution of input features over time while the relationship between features and target remains constant.

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Andrew Ng

AI educator and entrepreneur who co-founded Coursera and deeplearning.ai, making AI education accessible to millions worldwide.

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Mean Squared Error

The average of the squared differences between predicted and actual values. Emphasizes larger errors due to squaring.

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