rnx_auc_embed: Area Under the RNX Curve
In jlmelville/sneer: Stochastic Neighbor Embedding Experiments in R
rnx_auc_embed R Documentation
Area Under the RNX Curve
Description
The RNX curve is formed by calculating the rnx_crm metric for
different sizes of neighborhood. Each value of RNX is scaled according to
the natural log of the neighborhood size, to give a higher weight to smaller
neighborhoods. An AUC of 1 indicates perfect neighborhood preservation, an
AUC of 0 is due to random results.
Usage
rnx_auc_embed(din, dout)
Arguments
din
Input distance matrix.
dout
Output distance matrix.
Value
Area under the RNX curve.
References
Lee, J. A., Peluffo-Ordo'nez, D. H., & Verleysen, M. (2015).
Multi-scale similarities in stochastic neighbour embedding: Reducing
dimensionality while preserving both local and global structure.
Neurocomputing, 169, 246-261.
jlmelville/sneer documentation built on Nov. 15, 2022, 8:13 a.m.
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| rnx_auc_embed | R Documentation |
Area Under the RNX Curve
Description
The RNX curve is formed by calculating the rnx_crm metric for
different sizes of neighborhood. Each value of RNX is scaled according to
the natural log of the neighborhood size, to give a higher weight to smaller
neighborhoods. An AUC of 1 indicates perfect neighborhood preservation, an
AUC of 0 is due to random results.
Usage
rnx_auc_embed(din, dout)
Arguments
din |
Input distance matrix. |
dout |
Output distance matrix. |
Value
Area under the RNX curve.
References
Lee, J. A., Peluffo-Ordo'nez, D. H., & Verleysen, M. (2015). Multi-scale similarities in stochastic neighbour embedding: Reducing dimensionality while preserving both local and global structure. Neurocomputing, 169, 246-261.
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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