Statements (29)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Machine learning algorithm
Dimensionality reduction technique |
| gptkbp:appliesTo |
Nonlinear data
|
| gptkbp:basedOn |
Principal Component Analysis
|
| gptkbp:canUseKernel |
Gaussian kernel
Polynomial kernel Sigmoid kernel Linear kernel |
| gptkbp:category |
Unsupervised learning
|
| gptkbp:foundIn |
Principal components in high-dimensional feature space
|
| https://www.w3.org/2000/01/rdf-schema#label |
Kernel PCA
|
| gptkbp:implementedIn |
gptkb:MATLAB
gptkb:scikit-learn R |
| gptkbp:input |
Data matrix
|
| gptkbp:introduced |
gptkb:Bernhard_Schölkopf
|
| gptkbp:introducedIn |
1997
|
| gptkbp:output |
Transformed data
|
| gptkbp:relatedTo |
gptkb:Support_Vector_Machine
gptkb:t-SNE gptkb:Multidimensional_scaling |
| gptkbp:requires |
Kernel matrix
|
| gptkbp:usedFor |
Noise reduction
Data visualization Feature extraction Pattern recognition |
| gptkbp:uses |
Kernel trick
|
| gptkbp:bfsParent |
gptkb:Kernel_Principal_Component_Analysis
|
| gptkbp:bfsLayer |
8
|