Cardiovascular and Diabetes Diseases Classification Using Ensemble Stacking Classifiers with SVM as a Meta Classifier

. 2022 Oct 26;12(11):2595. doi: 10.3390/diagnostics12112595

Algorithm 1: The Proposed Stacking Model

1.
Start
2.
Input data: Input training dataset $X = {x_{i}, y_{i}}_{i = 1}^{m}$
3.
Output data: Stacking classifier output result.
4.
Pre-process the input data
5.
Set all the model architecture according to the input data
6.
Train all the base classifiers
7.
for t = 1 to T do
8.
learn $o u t p u t_{t}$ based on $X$
9.
end for
10.
Generate new dataset of the base classifiers
11.
For $i = 1 t o m d o$

$X_{b c} = {{x^{'}}_{b c}, y_{i}}$ where ${x^{'}}_{b c}$ = ${o u t p u t_{1 (x_{i})}, \dots \dots o u t p u t_{T (x_{i})}}$
12.
$e n d f o r$
13.
Learn SVM as a mate classifier in the proposed model
14.
Learn $y_{i}$ base on $X_{b c}$
15.
Generate the final output $Y_{i}$
16.
End