-
Notifications
You must be signed in to change notification settings - Fork 0
/
untitled2.asv
61 lines (54 loc) · 1.33 KB
/
untitled2.asv
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
%%
clc
clear all
cd("C:\Users\HP\Desktop\harit\multiscale_entropy\calculated_entropy\")
shannon_healthy = load('shannon_healthy.mat').shannon_healthy;
approx_healthy = load('approx_healthy.mat').approx_healthy;
permute_healthy = load('permute_healthy.mat').permute_healthy;
sample_healthy = load('sample_healthy.mat').sample_healthy;
renyi_healthy = load('renyi_healthy.mat').renyi_healthy;
%%
cd("C:\Users\HP\Desktop\harit\multiscale_entropy\sz_en\")
shannon_sz = load('shannon_sz.mat').shannon_sz;
approx_sz = load('approx_sz.mat').approx_sz;
permute_sz = load('permute_sz.mat').permute_sz;
sample_sz = load('sample_sz.mat').sample_sz;
renyi_sz = load('renyi_sz.mat').renyi_sz;
%% training_set
tTrain = zeros(2,1063);
j=1;
for i=1:485
xTrainImages{1,j}=sample_healthy{i,1};
tTrain(1,j)=1;
tTrain(2,j)=0;
j = j+1;
xTrainImages{1,j}=sample_sz{i,1};
tTrain(1,j)=0;
tTrain(2,j)=1;
j=j+1;
end
for i=517:610
xTrainImages{1,j}=sample_sz{i,1};
tTrain(1,j)=0;
tTrain(2,j)=1;
j=j+1;
end
%%
tTrain = zeros(2,79);
k =1;
for i=486:516
xTestImages{1,j}=sample_healthy{i,1};
tTest(1,j)=1;
tTest(2,j)=0;
j = j+1;
xTestImages{1,j}=sample_sz{i,1};
tTest(1,j)=0;
tTest(2,j)=1;
j=j+1;
end
for i=611:626
xTestImages{1,j}=sample_sz{i,1};
tTest(1,j)=0;
tTest(2,j)=1;
j=j+1;
end