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PCP Application 2.2

  Date Added: May 10, 2013  |  Visits: 294

PCP Application

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This application 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 The program supports interactive and batch processing. Commands are issued through a keyboard-driven menu system in the interactive mode, or in a batch file in the batch mode. It is a binary executable and does not need any special run-time environment. PCP uses tab-delimited text files for input data. The results are displayed on the screen and saved in text files.

Requirements: No special requirements
Platforms: Windows, Mac, *nix, Mac OSX, Linux, C/C++ , BSD Solaris
Keyword: Classification Of Patterns Learning Machine Machine Learning Program Patterns Classification Algorithm Program
Users rating: 0/10

License: Freeware
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