PCP (Pattern Classification Program) is an open-source machine learning program for supervised classification of patterns (vectors of measurements). PCP implements the following algorithms and methods: * Fisher's linear discriminant * dimensionality reduction using Singular Value Decomposition * Principal Component Analysis * feature subset selection * Bayes error estimation * parametric classifiers (linear and quadratic) * least-squares (pseudo-inverse) linear discriminant * k-Nearest Neighbor (k-NN) * neural networks (Multi-Layer Perceptron (MLP)) * Support Vector Machine (SVM) algorithm * SVM, MLP and k-NN model selection * cross-validation * bagging (committee) classification
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232 B
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5 lines
232 B
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$NetBSD: distinfo,v 1.1.1.1 2010/09/02 11:56:15 jihbed Exp $
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SHA1 (pcp-2.2.tar.gz) = 1ac8e0d795338645e55321c345eca53382870f08
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RMD160 (pcp-2.2.tar.gz) = c3606f5af124ed604d9d69eaa85719bb1a9f0d8e
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Size (pcp-2.2.tar.gz) = 2710238 bytes
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