An Epilepsy Detection Method Using Multiview Clustering Algorithm and Deep Features

Algorithm 1:

Input Data set , cluster number , parameters , , initialization iteration parameters , maximum iteration parameters , termination condition threshold

Output The membership matrix of the multiview data set that minimizes Eq. (1)

Step1 Randomly generated and normalized membership matrix of .

Step2 Repeat the following calculation process until the iteration termination condition is reached.

  For each

1) Calculate the clustering center of the -th view space according to Eq. (9);

2) According to Eq. (3)-(4), calculate the distance between the data and the cluster center in the p-dimensional space of the -th view; .....

3) Calculate the weight of the -th view space according to Eq. (11)-(12);

  End for

4) Calculate the membership of the data object according to Eq. (10)

5) 

Step3 Using Eqs. (10), (11) and (13) to generate a classifier and output the classification result.

Algorithm 1: