-
Notifications
You must be signed in to change notification settings - Fork 39
/
RunKMComp.m
126 lines (86 loc) · 4.28 KB
/
RunKMComp.m
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
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
function RunKMComp(DataSetStartIndex, DataSetEndIndex, DistanceIndex, Param1, Param2, Param1prime, Param2prime, Train, Test)
% Kernel Matrices for:
% 1 - SINK 20 Parameters (20 x 1)
% 2 - GAK 26 Parameters (26 x 1)
% 3 - KDTW 20 Parameters (20 x 1)
%
%
Methods = [cellstr('SINK'), 'GAK', 'KDTW'];
% first 2 values are '.' and '..' - UCR Archive 2018 version has 128 datasets
dir_struct = dir('./UCR2018/');
Datasets = {dir_struct(3:130).name};
% Sort Datasets
[Datasets, ~] = sort(Datasets);
%poolobj = gcp('nocreate');
%delete(poolobj);
%parpool(18);
addpath(genpath('lockstepmeasures/.'));
addpath(genpath('kernelmeasures/.'));
for i = 1:length(Datasets)
if (i>=DataSetStartIndex && i<=DataSetEndIndex)
disp(['Dataset being processed: ', char(Datasets(i))]);
DS = LoadUCRdataset(char(Datasets(i)));
[Params, Params2]= DistanceToParameter(DistanceIndex);
for w=Param1:Param2
for wprime = Param1prime:Param2prime
disp(w);
disp(wprime);
[NewParameter1, NewParameter2] = ComputeParameters(DS.Train, DistanceIndex, Params(w), Params2(wprime));
if Train==1
tic;
DM1 = KMComp(DS.Train, DistanceIndex, NewParameter1, NewParameter2);
RT1 = toc;
dlmwrite( strcat( './KM/',char(Datasets(i)),'/', char(Datasets(i)),'_',char(Methods(DistanceIndex)),'_', num2str(Params(w)),'_', num2str(Params2(wprime)), '_Train.distmatrix' ), DM1, 'delimiter', ',');
dlmwrite( strcat( './KM-Runtime/',char(Datasets(i)),'/', char(Datasets(i)),'_',char(Methods(DistanceIndex)),'_', num2str(Params(w)),'_', num2str(Params2(wprime)), '.rtTrain' ), RT1, 'delimiter', ',');
end
if Test==1
tic;
DM2 = KMComp_TestToTrain(DS.Test, DS.Train, DistanceIndex, NewParameter1, NewParameter2);
RT2 = toc;
dlmwrite( strcat( './KM/',char(Datasets(i)),'/', char(Datasets(i)),'_',char(Methods(DistanceIndex)),'_', num2str(Params(w)),'_', num2str(Params2(wprime)), '_TestToTrain.distmatrix' ), DM2, 'delimiter', ',');
dlmwrite( strcat( './KM-Runtime/',char(Datasets(i)),'/', char(Datasets(i)),'_',char(Methods(DistanceIndex)),'_', num2str(Params(w)),'_', num2str(Params2(wprime)), '.rtTestToTrain' ), RT2, 'delimiter', ',');
end
end
end
end
end
%poolobj = gcp('nocreate');
%delete(poolobj);
end
function [Params,Params2] = DistanceToParameter(DistanceIndex)
if DistanceIndex==1
% 1 - SINK 20 Parameters (20 x 1)
Params = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20];
Params2 = 0;
elseif DistanceIndex==2
% 2 - GAK 26 Parameters (26 x 1)
Params = [0.01,0.05,0.1,0.25,0.5,0.75,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20];
Params2 = 0;
elseif DistanceIndex==3
% 3 - KDTW 20 Parameters (20 x 1)
Params = [2^-15,2^-14,2^-13,2^-12,2^-11,2^-10,2^-9,2^-8,2^-7,2^-6,2^-5,2^-4,2^-3,2^-2,2^-1,2^0,2^1,2^2,2^3,2^4];
Params2 = 0;
end
end
function [NewParameter1, NewParameter2] = ComputeParameters(X, DistanceIndex, Parameter1, Parameter2)
[m, TSLength] = size(X);
if DistanceIndex==2
% GAK tuning as suggested in author's website
dists = [];
for l=1:10
rng(l);
x = X(ceil(rand*m),:);
y = X(ceil(rand*m),:);
w = [];
for p=1:TSLength
w(p)= ED(x(p),y(p));
end
dists=[dists,w];
end
NewParameter1 = Parameter1*median(dists)*sqrt(TSLength);
NewParameter2 = Parameter2;
else
NewParameter1 = Parameter1;
NewParameter2 = Parameter2;
end
end