runDS: Distance to the Trimmed Mean Classification Method

In RcmdrPlugin.depthTools: R Commander Depth Tools Plug-in

Description

Implementation of the classification technique based on assigning each observation to the group that minimizes the distance of the observation to the trimmed mean of the group.

Details

The user can choose the learning and test sets, as well as the labels corresponding to the learning set. The DS method proceeds by first computing the alpha trimmed mean corresponding to each group from the learning set, then computing the distance from a new observation to each trimmed mean. The new sample will then be assigned to the group that minimizes such distance. At the moment, only the Euclidean distance is implemented. The predicted labels can be stored as a vector.

Author(s)

Sara Lopez-Pintado [e-mail] and

Aurora Torrente [e-mail]

References

Lopez-Pintado, S. et al. (2010). Robust depth-based tools for the analysis of gene expression data. Biostatistics, 11 (2), 254-264.

See Also

computeTmean, runTAD

RcmdrPlugin.depthTools documentation built on Oct. 23, 2020, 5:49 p.m.