The function does a kernel projection regression. It returns a function which predicts labels for new data points.
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model |
list of rde data returned by |
X |
matrix containing the data points, only needed if |
Xname |
the name of the parameter of the kernel function which should contain the data points,
only needed if |
Yname |
the name of the parameter of the kernel function which should contain the 2nd data matrix |
kernel |
kernel function to use, only needed if |
regression |
set this to TRUE in case of a regression problem and to FALSE in case of a classification problem;
only needed if |
... |
parameters for the kernel function, only needed if |
function which predicts labels for new input data (gets a matrix with one data point per line)
Jan Saputra Mueller
M. L. Braun, J. M. Buhmann, K. R. Mueller (2008) \_On Relevant Dimensions in Kernel Feature Spaces\_
selectmodel
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