The accSDA package provides functions to perform sparse discriminant
analysis using a selection of three optimization methods,
proximal gradient (PG), accelerated proximal gradient (APG) and
alternating direction method of multipliers (ADMM). The package
is intended to extend the available tools to perform sparse
discriminant analysis in R. The three methods can be called
from the function
ASDA. Cross validation is also
implemented for the L1 regularization parameter. Functions
for doing predictions, summary, printing and simple plotting
are also provided. The sparse discriminant functions perform
lda on the projected data by default, using the lda function
in the MASS package. The functions return an object of the
same class as the name of the function and provide the lda
solution, along with the projected data, thus other kinds
of classification algorithms can be employed on the projected data.
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