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// $Id$ |
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/* |
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Copyright (C) 2004 Jari Häkkinen |
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Copyright (C) 2005 Jari Häkkinen, Peter Johansson |
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Copyright (C) 2006 Jari Häkkinen |
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This file is part of the thep c++ tools library, |
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http://lev.thep.lu.se/trac/c++_tools |
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|
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The c++ tools library is free software; you can redistribute it |
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and/or modify it under the terms of the GNU General Public License |
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as published by the Free Software Foundation; either version 3 of |
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the License, or (at your option) any later version. |
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|
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The c++ tools library is distributed in the hope that it will be |
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useful, but WITHOUT ANY WARRANTY; without even the implied warranty |
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of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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General Public License for more details. |
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You should have received a copy of the GNU General Public License |
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along with WeNNI. If not, see <http://www.gnu.org/licenses/>. |
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*/ |
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#ifndef _theplu_utility_knni_ |
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#define _theplu_utility_knni_ |
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#include <c++_tools/utility/NNI.h> |
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#include <iostream> |
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#include <vector> |
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namespace theplu { |
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namespace utility { |
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/// |
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/// kNNI is the binary weight implementation of NNI. This follows |
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/// the work done by Troyanskaya et al. cited in the NNI document |
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/// referred to in the NNI class documentation. |
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/// |
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/// This is a special case of the WeNNI, but is maintained since it |
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/// is faster than the more general WeNNI. |
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/// |
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/// @see NNI and WeNNI |
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/// |
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class kNNI : public NNI |
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{ |
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public: |
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/// |
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/// Constructor |
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/// |
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kNNI(const gslapi::matrix& matrix,const gslapi::matrix& weight, |
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const unsigned int neighbours); |
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/// |
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/// Perform kNNI on data in \a matrix with binary uncertainty |
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/// weights in \a weight using \a neighbours for the new impute |
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/// value. |
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/// |
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unsigned int estimate(void); |
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private: |
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std::vector<unsigned int> mv_rows_; // index to rows that have values to estimate |
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}; |
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}} // of namespace utility and namespace theplu |
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#endif |