Last change
on this file since 228 was
228,
checked in by Peter, 18 years ago
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moved estimation from constructor, added function telling which rows were not imputed (due too many missing values).
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Property svn:eol-style set to
native
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Property svn:keywords set to
Author Date Id Revision
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File size:
952 bytes
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1 | // $Id: WeNNI.h 228 2005-02-01 14:06:51Z peter $ |
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2 | |
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3 | #ifndef _theplu_cpptools_wenni_ |
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4 | #define _theplu_cpptools_wenni_ |
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5 | |
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6 | #include "NNI.h" |
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7 | |
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8 | #include <iostream> |
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9 | |
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10 | #include "matrix.h" |
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11 | |
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12 | namespace theplu { |
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13 | namespace cpptools { |
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14 | |
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15 | using namespace std; |
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16 | |
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17 | /// |
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18 | /// WeNNI is a continuous weights generalization of the (binary |
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19 | /// weights) kNNI algorithm presented by Troyanskaya et al. A |
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20 | /// reference to this paper is found in the NNI document referred to |
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21 | /// in the NNI class documentation. The NNI document also describes |
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22 | /// WeNNI in depth. |
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23 | /// |
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24 | /// @see NNI and kNNI |
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25 | /// |
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26 | class WeNNI : public NNI |
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27 | { |
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28 | public: |
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29 | /// |
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30 | /// Constructor |
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31 | /// |
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32 | WeNNI(const gslapi::matrix& matrix,const gslapi::matrix& weight, |
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33 | const u_int neighbours); |
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34 | |
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35 | /// |
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36 | /// Perform WeNNI on data in \a matrix with continuous uncertainty |
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37 | /// weights in \a weight using \a neighbours for the new impute |
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38 | /// value. |
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39 | /// |
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40 | u_int estimate(void); |
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41 | |
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42 | private: |
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43 | |
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44 | |
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45 | }; |
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46 | |
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47 | }} // of namespace cpptools and namespace theplu |
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48 | |
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49 | #endif |
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