Quadratic Discriminant Analysis
Quadratic discriminant analysis is a generative classifier that models each class with its own multivariate Gaussian distribution, allowing each class a separate covariance matrix. Unlike linear discriminant analysis, which assumes a shared covariance and yields linear boundaries, QDA's per-class covariances produce curved (quadratic) decision boundaries, letting it capture differences in the spread and orientation of the classes.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning (2nd ed.). Springer. · ISBN 978-0-387-84857-0
- James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning. Springer. · ISBN 978-1-4614-7138-7
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
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Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.