Package: dml 1.1.0.9001

dml: Distance Metric Learning in R

State-of-the-art algorithms for distance metric learning, including global and local methods such as Relevant Component Analysis, Discriminative Component Analysis, Local Fisher Discriminant Analysis, etc. These distance metric learning methods are widely applied in feature extraction, dimensionality reduction, clustering, classification, information retrieval, and computer vision problems.

Authors:Yuan Tang [aut, cre], Tao Gao [aut], Nan Xiao [aut]

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NEWS

Peer review:

Bug tracker:https://github.com/terrytangyuan/dml/issues

On CRAN:

dimensionality-reductiondistance-metric-learningmachine-learningmetric-learningstatistics

4 exports 58 stars 3.56 score 8 dependencies 1 dependents 8 scripts 205 downloads

Last updated 1 years agofrom:68558d8b81. Checks:OK: 1 ERROR: 6. Indexed: yes.

Exports:dcaGdmDiagGdmFullrca

Dependencies:latticelfdaMatrixplyrrARPACKRcppRcppEigenRSpectra