Skip to content

add package msPCA #45

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
LucasKook wants to merge 1 commit into
base: main
Choose a base branch
from
Open

add package msPCA #45

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
7 changes: 5 additions & 2 deletions MachineLearning.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@ name: MachineLearning
topic: Machine Learning & Statistical Learning
maintainer: Torsten Hothorn, Hannah Frick, Lucas Kook
email: Torsten.Hothorn@R-project.org
version: 2026-06-05
version: 2026-07-14
source: https://github.com/cran-task-views/MachineLearning/
---

Expand Down Expand Up @@ -150,7 +150,10 @@ roughly structured into the following topics:
reliable p-values for all model parameters. Best-subset selection
for linear, logistic, Cox and other regression models, based on a
fast polynomial time algorithm, is available from package
`r pkg("abess", priority = "core")`.
`r pkg("abess", priority = "core")`. Sparse principal component
analysis with multiple components, providing regularized
unsupervised dimension reduction for high-dimensional data, is
implemented in package `r pkg("msPCA")`.
- *Boosting and Gradient Descent* : Various forms of gradient boosting
are implemented in package
`r pkg("gbm", priority = "core")` (tree-based functional
Expand Down