vec_shrink

<p>Applies softmax the soft thresholding shrinkage operator to v with tolerance a.
That is, output is the vector with entries with absolute value v_i - a if
|v_i| &gt; a and zero otherwise, with sign pattern matching that of v.</p>

internal

Implementation of sparse linear discriminant analysis, which is a supervised
classification method for multiple classes. Various novel optimization approaches to
this problem are implemented including alternating direction method of multipliers (ADMM),
proximal gradient (PG) and accelerated proximal gradient (APG) (See Atkins et al. <arXiv:1705.07194>).
Functions for performing cross validation are also supplied along with basic prediction
and plotting functions.
Sparse zero variance discriminant analysis (SZVD) is also included in the package
(See Ames and Hong, <arXiv:1401.5492>). See the github wiki for a more extended description.

Gudmundur Einarsson

accSDA

Accelerated Sparse Discriminant Analysis

Line Clemmensen

Brendan Ames

Summer Atkins

vec_shrink function

Softmax for SZVD ADMM iterations — vec_shrink

Softmax for SZVD ADMM iterations

vec_shrink: Softmax for SZVD ADMM iterations

Description

Usage

Arguments

Value

Details

See Also