Safe Semi-Supervised Learning Tools
Overview
Implements several safe graph-based semi-supervised learning algorithms. The first algorithm is the Semi-Supervised Semi-Parametric Model (S4PM) and the fast Anchor Graph version of this approach. For additional technical details, refer to Culp and Ryan (2013) http://jmlr.org/papers/v14/culp13a.html, Ryan and Culp (2015) http://www.jmlr.org/papers/v16/ryan15a.html and the package vignette. The underlying fitting routines are executed in C++. All tuning parameter estimation is optimized using K-fold Cross-Validation.
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Documentation
- Help pages
- 18
- Examples that run
- 89%8 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 42%
- Documented parameters
- 97%
- Return-value docs
- 33%
- Help pages citing references
- 17%
Also includes 1 demo script (run with demo())
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Dependencies
Code & Tests
Datasets
People & History
- RR 3.6.0 released · 2019-04-26
- archivedRemoved from CRAN2018-06-28long-standing check errors were not corrected despite reminder Invalid reads in gcc's ASAN and valgrind
- 1.02018-05-11
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2018-05-11
- Total releases
- 1 / 8 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 203 KB / 1 file
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