1 | // $Id: NNI.h 241 2005-02-22 11:30:25Z jari $ |
---|
2 | |
---|
3 | #ifndef _theplu_cpptools_nni_ |
---|
4 | #define _theplu_cpptools_nni_ |
---|
5 | |
---|
6 | #include <iostream> |
---|
7 | #include <utility> |
---|
8 | #include <vector> |
---|
9 | |
---|
10 | #include "matrix.h" |
---|
11 | |
---|
12 | namespace theplu { |
---|
13 | namespace cpptools { |
---|
14 | |
---|
15 | using namespace std; |
---|
16 | |
---|
17 | /// |
---|
18 | /// NNI is an abstract base class defining the interface for nearest |
---|
19 | /// neighbour imputation (NNI) algorithms. |
---|
20 | /// |
---|
21 | /// NNI algorithms implemented here is discussed in documents |
---|
22 | /// created in the WeNNI project. This document will be released for |
---|
23 | /// public access, and the necessary information for retrieving that |
---|
24 | /// document will be provided here. |
---|
25 | /// |
---|
26 | /// Short introduction to NNI is that one may want to improve |
---|
27 | /// (correct) uncertain data. Here, the data to be imputed is stored in a |
---|
28 | /// matrix where rows similar to each other are used to adjust |
---|
29 | /// uncertain data. The data matrix is accompanied by a weight |
---|
30 | /// (uncertainty) matrix defining what data is to be considered as |
---|
31 | /// 'certain' and what data is uncertain. The weight matrix can be |
---|
32 | /// binary with 1's indicating that the data does not need |
---|
33 | /// corrections, whereas a 0 means that the data should be replaced |
---|
34 | /// by an imputed value. Naturally, the weight matrix can also be |
---|
35 | /// continuous where values between 0 and 1 defines how certain a |
---|
36 | /// data element is. |
---|
37 | /// |
---|
38 | /// The imputation depends on how similarity of rows of data is |
---|
39 | /// defined and on the number of closest neighbours (here; rows) to |
---|
40 | /// use in the imputation can be set. |
---|
41 | /// |
---|
42 | /// Implementation issues |
---|
43 | /// |
---|
44 | /// The current implementation treats rows where all data are tagged |
---|
45 | /// are completely uncertain, i.e. all weights are zero, by |
---|
46 | /// ignoring these lines in nearest neighbourhood |
---|
47 | /// calculations. Importantly, this type of data are not changed |
---|
48 | /// (imputed) either since there is no close neighbourhood defined |
---|
49 | /// for this data. |
---|
50 | /// |
---|
51 | /// Rows that is completely identical in an imputation algorithm |
---|
52 | /// sense will give problems since the distance between will usually |
---|
53 | /// become zero. This is solved by setting zero distance to a small |
---|
54 | /// number. Identical rows in this context are basically a |
---|
55 | /// comparison between elements with non-zero uncertainty weights |
---|
56 | /// only, and all these elements are equal. Zero weight elements are |
---|
57 | /// not used in the comparison since these are considered as |
---|
58 | /// non/sense values. |
---|
59 | /// |
---|
60 | class NNI |
---|
61 | { |
---|
62 | public: |
---|
63 | |
---|
64 | /// |
---|
65 | /// Base constructor for the nearest neighbour imputation |
---|
66 | /// algorithms. |
---|
67 | /// |
---|
68 | NNI(const gslapi::matrix& matrix,const gslapi::matrix& weight, |
---|
69 | const u_int neighbours); |
---|
70 | |
---|
71 | virtual ~NNI(void) {}; |
---|
72 | |
---|
73 | /// |
---|
74 | /// Function doing the imputation. |
---|
75 | /// |
---|
76 | /// @return number of rows not imputed |
---|
77 | /// |
---|
78 | virtual u_int estimate(void)=0; |
---|
79 | |
---|
80 | /// |
---|
81 | /// @return A const reference to the modified data. |
---|
82 | /// |
---|
83 | const gslapi::matrix& imputed_data(void) const { return imputed_data_; } |
---|
84 | |
---|
85 | /// |
---|
86 | /// @return indices of rows in data matrix not imputed |
---|
87 | /// |
---|
88 | inline vector<size_t> not_imputed(void) const { return not_imputed_; } |
---|
89 | |
---|
90 | protected: |
---|
91 | vector<pair<u_int,double> > calculate_distances(const u_int) const; |
---|
92 | vector<u_int> nearest_neighbours(const u_int, |
---|
93 | const vector<pair<u_int,double> >&) const; |
---|
94 | |
---|
95 | const gslapi::matrix& data_; |
---|
96 | gslapi::matrix imputed_data_; |
---|
97 | u_int neighbours_; |
---|
98 | vector<size_t> not_imputed_; |
---|
99 | const gslapi::matrix& weight_; |
---|
100 | }; |
---|
101 | |
---|
102 | }} // of namespace cpptools and namespace theplu |
---|
103 | |
---|
104 | #endif |
---|