Usporedite metode
Pregledajte odabrane metode jednu uz drugu; retci koji se razlikuju su istaknuti.
| Stroj potpornih vektora (klasifikacija)× | K-Najbližih Susjeda× | |
|---|---|---|
| Područje | Strojno učenje | Strojno učenje |
| Obitelj | Machine learning | Machine learning |
| Godina nastanka≠ | 1995 | 1967 |
| Tvorac≠ | Cortes, C. & Vapnik, V. | Cover, T.M. & Hart, P.E. |
| Vrsta≠ | Maximum-margin classifier (kernel method) | Instance-based (non-parametric) learning |
| Temeljni izvor≠ | Cortes, C. & Vapnik, V. (1995). Support-Vector Networks. Machine Learning, 20, 273–297. DOI ↗ | Cover, T.M. & Hart, P.E. (1967). Nearest Neighbor Pattern Classification. IEEE Transactions on Information Theory, 13(1), 21–27. DOI ↗ |
| Drugi nazivi | Destek Vektör Makinesi (SVM — Sınıflandırma), support-vector network, SVM classifier, maximum-margin classifier | KNN, K-En Yakın Komşu (KNN), nearest neighbor classifier, instance-based learning |
| Srodne | 5 | 5 |
| Sažetak≠ | The Support Vector Machine, introduced by Corinna Cortes and Vladimir Vapnik in 1995, is a classifier that finds the optimal separating hyperplane between classes in a high-dimensional space. It chooses the boundary that leaves the widest possible margin to the nearest training points, which makes its decisions robust on new data. | K-Nearest Neighbors (KNN), formalized by Cover and Hart in 1967, is a non-parametric, instance-based method that classifies or predicts a new observation by looking at the k closest examples in the training data. For classification it takes a majority vote among those neighbors; for regression it averages their values. |
| ScholarGateSkup podataka ↗ |
|
|