Package: cpfa
Type: Package
Title: Classification with Parallel Factor Analysis
Version: 1.0-4
Date: 2022-06-20
Author: Matthew A. Snodgress <snodg031@umn.edu>
Maintainer: Matthew A. Snodgress <snodg031@umn.edu>
Depends: multiway, glmnet, e1071, randomForest, nnet
Imports: foreach, doParallel
Description: Classification using Richard A. Harshman's Parallel Factor Analysis (Parafac) model-1 fit to a three-way or four-way data tensor/array. See Harshman and Lundy (1994): <doi:10.1016/0167-9473(94)90132-5>. Uses Parafac factor weights from one mode of this model as predictors to tune parameters for one or more classification methods via a k-fold cross-validation procedure. Supports penalized logistic regression, support vector machine, random forest, and feed-forward neural network. Supports binary and multiclass classification. Predicts class labels or class probabilities and calculates multiple classification performance measures. Parallel computing is implemented via the 'parallel' and 'doParallel' packages.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2022-06-20 13:29:08 UTC; snodg031
Repository: CRAN
Date/Publication: 2022-06-20 14:20:06 UTC
Built: R 4.1.2; ; 2022-06-21 10:35:53 UTC; unix
