TestDependenciesCommand.h

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// -*- C++ -*-

// TestDependenciesCommand.h
// 
// Copyright (C) 2003 Pascal Vincent
// 
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
// 
//  1. Redistributions of source code must retain the above copyright
//     notice, this list of conditions and the following disclaimer.
// 
//  2. 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.
// 
//  3. The name 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 BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
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// 
// This file is part of the PLearn library. For more information on the PLearn
// library, go to the PLearn Web site at www.plearn.org

/* *******************************************************      
   * $Id: TestDependenciesCommand.h,v 1.3 2004/02/20 21:11:40 chrish42 Exp $ 
   ******************************************************* */

#ifndef TestDependenciesCommand_INC
#define TestDependenciesCommand_INC

#include "PLearnCommand.h"
#include "PLearnCommandRegistry.h"

namespace PLearn {
using namespace std;

class TestDependenciesCommand: public PLearnCommand
{
public:
  TestDependenciesCommand():
    PLearnCommand("test-dependencies",
                  "Compute dependency statistics between input and target variables.",
                  "  test-dependencies <VMat> [<inputsize> <targetsize> [<datablocksize>]]\n"
                  "Reads a VMatrix (or any matrix format) and computes dependency statistics between each\n"
                  "of the input variables and each of the target variables. A dependency score is then\n"
                  "computed and a report is produced, listing the input variables in decreasing value of\n"
                  "that score. The current implementation only computes the Spearman rank correlation\n"
                  "and the linear correlation. If <datablocksize> is provided, it is used to\n"
                  "divide the data row-wise in blocks of <datablocksize> rows. The statistics\n"
                  "are computed separately in each block, and then some statistics of these\n"
                  "statistics (min, max, mean, stdev) are reported.\n")
  {}
                    
  virtual void run(const vector<string>& args);

protected:
  static PLearnCommandRegistry reg_;
};

  
} // end of namespace PLearn

#endif

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