1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
|
function [cmb association] = IAMB( data, targetindex, THRESHOLD)
%function [cmb association] = IAMB( data, targetindex, THRESHOLD)
%
%Performs the IAMB algorithm of Tsmardinos et al. (2003)
%from "Towards principled feature selection: Relevancy, filters and wrappers"
if (nargin == 2)
THRESHOLD = 0.02;
end
numf = size(data,2);
targets = data(:,targetindex);
data(:,targetindex) = -10;
cmb = [];
finished = false;
while ~finished
for n = 1:numf
cmbVector = joint(data(:,cmb));
if isempty(cmb)
association(n) = mi( data(:,n), targets );
end
if ismember(n,cmb)
association(n) = -10; %arbtirary large negative constant
else
association(n) = cmi( data(:,n), targets, cmbVector);
end
end
[maxval maxidx] = max(association);
if maxval < THRESHOLD
finished = true;
else
cmb = [ cmb maxidx ];
end
end
finished = false;
while ~finished && ~isempty(cmb)
association = [];
for n = 1:length(cmb)
cmbwithoutn = cmb;
cmbwithoutn(n)=[];
association(n) = cmi( data(:,cmb(n)), targets, data(:,cmbwithoutn) );
end
[minval minidx] = min(association);
if minval > THRESHOLD
finished = true;
else
cmb(minidx) = [];
end
end
|
