PCP
PCP
http://pcp.sourceforge.net/
Machine learning program for pattern classification
PCP (Pattern Classification Program) is an machine learning program for supervised and unsupervised classification of patterns. It runs in interactive and batch modes, and implements the following machine learning algorithms and methods:
- k-means clustering
- Fisher's linear discriminant
- Singular Value Decomposition
- Principal Component Analysis
- feature subset selection
- Bayes error estimation
- parametric classifiers (linear and quadratic)
- pseudo-inverse linear discriminant
- k-Nearest Neighbor method
- neural networks
- Support Vector Machine algorithm
- cross-validation
- bagging (committee) classification
Licensing
License
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Notes
Leaders and contributors
Contact(s) | Role |
---|---|
Ljubomir Buturovic | Maintainer |
Resources and communication
Audience | Resource type | URI |
---|---|---|
Bug Tracking,Developer,Support | mailto:ljubomir@sfsu.edu |
Software prerequisites
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