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📄 main.cpp

📁 Gaussian Mixture Algorithm
💻 CPP
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/*************************************************************************** *   Copyright (C) 2008 by Cyril Poulet   * *   cyril.poulet@centraliens.net   * * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are met: *     * Redistributions of source code must retain the above copyright *       notice, this list of conditions and the following disclaimer. *     * Redistributions in binary form must reproduce the above copyright *       notice, this list of conditions and the following disclaimer in the *       documentation and/or other materials provided with the distribution. *     * Redistribution under a license not approved by the Open Source *       Initiative (http://www.opensource.org) must display the *       following acknowledgement in all advertising material: *        This product includes software developed at the Courant *        Institute of Mathematical Sciences (http://cims.nyu.edu). *     * The names of the authors may not be used to endorse or promote products *       derived from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESS OR IMPLIED * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE * DISCLAIMED. IN NO EVENT SHALL ThE AUTHORS BE LIABLE FOR ANY * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. ***************************************************************************/#include "preprocess.h"#include "spex.h"//! this global variable is the number of data samples that will be loaded in//! the training database.intg trainsize = 10000;//! the first argument is the path to the data ( ../eblearn/demos/sp_Doc_classifier/data//! if you follow the instructions in the Readme), the second argument is optional ://! write "true" if you need to preprocess the data (the first time you use//! the application)int main(int argc, const char **argv){	string path;	bool preproc = false;	for (int i=1; i<argc; i++)	{		const char *arg = argv[i];		if(i == 1) path = arg;		if(i == 2){			if(arg == "true") preproc = true;		}	}	if(preproc) preprocess(path);	string trainfile = path + "/test.dat.gz";	sptrainer mytrainer(trainfile);	mytrainer.train(1);	return 0;}

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