Class "PredictSosDisc" - prediction of "SosDisc" objects
Class "PredictSosDisc" - prediction of "SosDisc" objects
The prediction of a "SosDisc" object
1.1
class
Objects from the Class
Objects can be created by calls of the form new("PredictSosDisc", ...)
but most often by invoking predict() on a "SosDisc" object. They contain values meant for printing by show()
Slots
classification:: Object of class "factor" representing the predicted classification
mahadist2:: A "matrix" containing the squared robust Mahalanobis distances to each group center in the subspace (see Details).
w:: A "vector" containing the weights derived from robust Mahalanobis distances to the closest group center (see Details).
Details
For the prediction of the class membership a two step approach is taken. First, the newdata are scaled and centered (by obj@scale and obj@center) and multiplied by obj@beta for dimension reduction. Then the classification of the transformed data is obtained by prediction with the Linda object obj@fit. The Mahalanobis distances to the closest group center in this subspace is used to derive case weights w. Observations where the squared robust mahalanobis distance is larger than the 0.975 quantile of the chi-square distribution with Q degrees of freedom receive weight zero, all others weight one.
Methods
show: signature(object = "PredictSosDisc"): Prints the results.
References
Clemmensen L, Hastie T, Witten D & Ersboll B (2012), Sparse discriminant analysis. Technometrics, 53 (4), 406--413.
Ortner I, Filzmoser P & Croux C (2020), Robust and sparse multigroup classification by the optimal scoring approach. Data Mining and Knowledge Discovery 34 , 723--741. tools:::Rd_expr_doi("10.1007/s10618-019-00666-8") .