方法证据记录
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Quadratic Discriminant Analysis (QDA)
分类方法记录 · latent-structure / machine-learning
- 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
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