cs229final/App_Prep.m at master · aashnashroff/cs229final · GitHub

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
%This file imports the cortex - averaged data and builds a matrix for the
%classifier App

X_D2_T2_test = importdata('D2_T2_cortex_2.mat');
X_D2_T2_train = importdata('D2_T2_cortex_10.mat');
X_D3_T3_test = importdata('D3_T3_cortex_2.mat');
X_D3_T3_train = importdata('D3_T3_cortex_10.mat');
X_PD2_H32_test = importdata('PD2_H32_cortex_2.mat');
X_PD2_H32_train = importdata('PD2_H32_cortex_10.mat');


%D
X_d = cat(1,X_D2_T2_train,X_D3_T3_train ,X_PD2_H32_train);
y_0 = zeros(1,1873);
y_1 = ones(1,1822);
y_2 = [];
y_2(1, 1:1808) = 2;
y_d = cat(2,y_0,y_1,y_2);

X_d_test = cat(1,X_D2_T2_test,X_D3_T3_test,X_PD2_H32_test);
y_0 = zeros(1,365);
y_1 = ones(1,377);
y_2 = [];
y_2(1, 1:374) = 2;
y_d_test = cat(2,y_0,y_1,y_2);

%shuffle train
perm = randperm(size(X_d,1));
X_d = X_d(perm, :);
y_d = y_d';
y_d = y_d(perm, :);


%make structload
data_d = array2table(X_d);
data_d.Group = y_d;

%Now, run a classifier and then export it