Q_NX: The Q_{NX}(K) criterion
In gdkrmr/coRanking: Co-Ranking Matrix
Q_NX R Documentation
The Q_{NX}(K) criterion
Description
A curve indicating the percentage of points that are mild in- and extrusions
or keep their rank.
Usage
Q_NX(Q)
Arguments
Q
a co-ranking matrix
Details
Q_{NX}(K) = \frac{1}{KN} \sum_{k=1}^{K}\sum_{l=1}^{K}Q_{kl}
Value
A vector with the values for Q_NX(K)
Author(s)
Guido Kraemer
References
Lueks, W., Mokbel, B., Biehl, M., & Hammer, B. (2011). How to
Evaluate Dimensionality Reduction? - Improving the Co-ranking Matrix.
ArXiv:1110.3917 [Cs]. http://arxiv.org/abs/1110.3917
gdkrmr/coRanking documentation built on March 23, 2023, 5:43 a.m.
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.
| Q_NX | R Documentation |
The Q_{NX}(K) criterion
Description
A curve indicating the percentage of points that are mild in- and extrusions or keep their rank.
Usage
Q_NX(Q)
Arguments
Q |
a co-ranking matrix |
Details
Q_{NX}(K) = \frac{1}{KN} \sum_{k=1}^{K}\sum_{l=1}^{K}Q_{kl}
Value
A vector with the values for Q_NX(K)
Author(s)
Guido Kraemer
References
Lueks, W., Mokbel, B., Biehl, M., & Hammer, B. (2011). How to Evaluate Dimensionality Reduction? - Improving the Co-ranking Matrix. ArXiv:1110.3917 [Cs]. http://arxiv.org/abs/1110.3917
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.