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/* * LC-3b identifier recognition and instruction handling * * Copyright (C) 2003 Peter Johnson * * Redistribution and use in source and binary forms, with or without * modification, are permi

%Pattern Recognition Tools (PRTOOLS 3.1.7) % Version 1 February 2002 (after PRSD course) % %Datasets and Mappings %--------------------- %dataset Define and retrieve dataset from datamatrix and la

%Pattern Recognition Tools (PRTOOLS 3.1.7) % Version 1 February 2002 (after PRSD course) % %Datasets and Mappings %--------------------- %dataset Define and retrieve dataset from datamatrix and la

% Statistical Pattern Recognition Toolbox (STPRtool). % Version 2.05 19-Oct-2005 % % Bayesian classification. % bayescls - Bayesian classifier with reject option. % bayesdf

% Statistical Pattern Recognition Toolbox (STPRtool). % Version 2.04 22-Dec-2004 % % Bayesian classification. % bayescls - Bayesian classifier with reject option. % bayesdf

% Statistical Pattern Recognition Toolbox (STPRtool). % Version 2.06 18-Sep-2006 % % Bayesian classification. % bayescls - Bayesian classifier with reject option. % bayesdf

% Statistical Pattern Recognition Toolbox (STPRtool). % Version 2.04 22-Dec-2004 % % Bayesian classification. % bayescls - Bayesian classifier with reject option. % bayesdf

/* * recognize.h - Type recognition support for Essence * * recognize.h,v 1.11 1995/09/05 19:11:33 hardy Exp * * ---------------------------------------------------------------------- * Copy

%Test the distribution of sparse correlations for sparse KCCA clear all; dataSet = 'letter-recognition.data'; [X, y, numExamples, numFeatures] = readCsvData(dataSet); %convert to indicator

%Test the distribution of sparse correlations for sparse KCCA clear all; dataSet = 'letter-recognition.data'; [X, y, numExamples, numFeatures] = readCsvData(dataSet); %convert to indicator