distInPCAspace: distInPCAspace
In EngeLab/kNNclassification: Unsupervised classification via k-Nearest-Neighbors and graph-based Louvain community detection
Description
Usage
Arguments
Author(s)
Description
Calculates Euclidean distance in PCA space.
Usage
1
distInPCAspace(pca, pcs)
Arguments
pca
Matrix; Principal components as columns, samples as rows.
pcs
Integer; Length 1 vector indicating the max principal component to
retain.
Author(s)
Jason T. Serviss
EngeLab/kNNclassification documentation built on May 5, 2019, 9:43 p.m.
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Description Usage Arguments Author(s)
Description
Calculates Euclidean distance in PCA space.
Usage
1 | distInPCAspace(pca, pcs)
|
Arguments
pca |
Matrix; Principal components as columns, samples as rows. |
pcs |
Integer; Length 1 vector indicating the max principal component to retain. |
Author(s)
Jason T. Serviss
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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