kmatrixGauss: Estimating Gaussian Kernel matrix
In DA: Discriminant Analysis for Evolutionary Inference
Description
Usage
Arguments
Details
Value
References
Description
This function estimates Gaussian kernel computation for klfda, which maps the original data space to non-linear and higher dimensions. See the deatils of kmatrixGauss from lfda.
Usage
1
kmatrixGauss(x, sigma = 1)
Arguments
x
Input data matrix or dataframe
sigma
The Gaussian kernel parameter
Details
Return a n*n matrix
Value
Return a n*n matrix
References
Tang, Y., & Li, W. (2019). lfda: Local Fisher Discriminant Analysis inR. Journal of Open Source Software, 4(39), 1572.
DA documentation built on July 12, 2021, 9:07 a.m.
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Description Usage Arguments Details Value References
Description
This function estimates Gaussian kernel computation for klfda, which maps the original data space to non-linear and higher dimensions. See the deatils of kmatrixGauss from lfda.
Usage
1 | kmatrixGauss(x, sigma = 1)
|
Arguments
x |
Input data matrix or dataframe |
sigma |
The Gaussian kernel parameter |
Details
Return a n*n matrix
Value
Return a n*n matrix
References
Tang, Y., & Li, W. (2019). lfda: Local Fisher Discriminant Analysis inR. Journal of Open Source Software, 4(39), 1572.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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