ANMM: Average Neighborhood Margin Maximization (ANMM).
In jlsuarezdiaz/rDML: Distance Metric Learning Algorithms for R
Description
Usage
Arguments
Value
References
Description
A DML Algorithm that obtains a transformer that maximizes the distance between the nearest friends and the nearest enemies for each example.
Usage
1
Arguments
num_dims
Dimension desired for the transformed data. Integer. If NULL, all features will be taken. Integer.
n_friends
Number of nearest same-class neighbors to compute homogeneus neighborhood. Integer.
n_enemies
Number of nearest different-class neighbors to compute heterogeneus neigborhood. Integer.
Value
The ANMM transformer, structured as a named list.
References
Fei Wang and Changshui Zhang. “Feature extraction by maximizing the average neighborhood
margin”. In: Computer Vision and Pattern Recognition, 2007. CVPR’07. IEEE Conference on.
IEEE. 2007, pages 1-8.
jlsuarezdiaz/rDML documentation built on May 24, 2019, 12:35 a.m.
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Description Usage Arguments Value References
Description
A DML Algorithm that obtains a transformer that maximizes the distance between the nearest friends and the nearest enemies for each example.
Usage
1 |
Arguments
num_dims |
Dimension desired for the transformed data. Integer. If NULL, all features will be taken. Integer. |
n_friends |
Number of nearest same-class neighbors to compute homogeneus neighborhood. Integer. |
n_enemies |
Number of nearest different-class neighbors to compute heterogeneus neigborhood. Integer. |
Value
The ANMM transformer, structured as a named list.
References
Fei Wang and Changshui Zhang. “Feature extraction by maximizing the average neighborhood margin”. In: Computer Vision and Pattern Recognition, 2007. CVPR’07. IEEE Conference on. IEEE. 2007, pages 1-8.
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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