Prototype methods
Prototype methods are machine learning methods that use data prototypes.[1] A data prototype is a data value that reflects other values in its class,[2] e.g., the centroid in a K-means clustering problem.
Methods
[edit]The following are some prototype methods[3]
Related Methods
[edit]While K-nearest neighbor's does not use prototypes, it is similar to prototype methods like K-means clustering.[4]
References
[edit]- ↑ Hastie, Trevor. The elements of statistical learning : data mining, inference, and prediction. Tibshirani, Robert,, Friedman, J. H. (Jerome H.) (Second ed.). New York. p. 459. ISBN 9780387848570. OCLC 300478243.
- ↑ Molnar, Christoph. 6.3 Prototypes and Criticisms | Interpretable Machine Learning.
- ↑ Hastie, Trevor. The elements of statistical learning : data mining, inference, and prediction. Tibshirani, Robert,, Friedman, J. H. (Jerome H.) (Second ed.). New York. pp. 459–463. ISBN 9780387848570. OCLC 300478243.
- ↑ Hastie, Trevor. The elements of statistical learning : data mining, inference, and prediction. Tibshirani, Robert,, Friedman, J. H. (Jerome H.) (Second ed.). New York. p. 465. ISBN 9780387848570. OCLC 300478243.
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