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mondejar / ecg-classification

Code for training and test machine learning classifiers on MIT-BIH Arrhyhtmia database
GNU General Public License v3.0
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Improve Results #6

Closed banivyom closed 5 years ago

banivyom commented 5 years ago

Right now I'm using single SVM with C_value = {0.001, 0.01, 0.1, 1, 10, 100} and oversampling(SMOTE) the train data, gamma_value=0.0 but the sensitivity for S and F class is very low. I read your paper and it says that Ensemble of SVMs with product rule will give good results. Can you please suggest any resources that I can use to implement this in python as I'm finding it difficult? Best result obtained till now: Ijk: 0.5552 Ij: 2.2895 Cohen's Kappa: 0.5380

Confusion Matrix:

[39988 1621 821 1603] [902 693 434 21] [ 113 16 3088 3] [249 1 102 36]

Overall ACC: 0.8815

mean Acc: 0.9408 mean Recall: 0.5745 mean Precision: 0.4959 N:

Sens: 0.9081 Prec: 0.9694 Acc: 0.8932 SVEB:

Sens: 0.3380 Prec: 0.2973 Acc: 0.9397 VEB:

Sens: 0.9590 Prec: 0.6952 Acc: 0.9701 F:

Sens: 0.0928 Prec: 0.0216 Acc: 0.9602

mondejar commented 5 years ago

Check the file /python/basic_fusion.py of this repository. In order to run the ensemble you have to train and run several SVM models, each one with a different feature, and then combine their decisions with this code.

banivyom commented 5 years ago

One more and the last thing left is to implement SVM+PSO. Can you provide some resources I can make use of, because as of now I learned about pyswarms library but unable to go further with this.. Any tiny help will be appreciated sir.