20 lines
691 B
Plaintext
20 lines
691 B
Plaintext
PCP (Pattern Classification Program) is an open-source
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machine learning program for supervised classification
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of patterns (vectors of measurements).
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PCP implements the following algorithms and methods:
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* Fisher's linear discriminant
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* dimensionality reduction using Singular Value Decomposition
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* Principal Component Analysis
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* feature subset selection
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* Bayes error estimation
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* parametric classifiers (linear and quadratic)
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* least-squares (pseudo-inverse) linear discriminant
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* k-Nearest Neighbor (k-NN)
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* neural networks (Multi-Layer Perceptron (MLP))
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* Support Vector Machine (SVM) algorithm
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* SVM, MLP and k-NN model selection
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* cross-validation
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* bagging (committee) classification
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