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When I delete all pickle files and then edit the load_MITBIH.py to include the fifth(Q) class, only 4 classes get included and not the fifth. I have also updated the evaluation_AAMI.py for confusion matrix for 5 class, but fifth row and column contains 0 always.
I'm taking window size of 180 centred at R-peak.

What should I do?

In your python version, it read the data under the scikit folder. However, there is no mention about how to generate these data. Did I miss something?

''Two median filters are applied for this purpose, of 200-ms and 600-ms. Note that this values depend on the frequency sampling of the signal.
from scipy.signal import medfilt
...

# median_filter1D
baseline = medfilt(MLII, 71) 
baseline = medfilt(baseline, 215) 

''
How to compute this values according to my frequency sampling? And what's your frequency sampling?

While running the run_train_svm.py file there is an error that occurs due to a file named load_MITBIH.py there the error which occurs is that the label given as 'w' is not found as the training set is DS_1.csv and there is no such label as w in that file.

Looking for response.

Error:
writing pickle: C:/Users/qasim/Desktop/jibran/ecg-classification-master/python/mit_db/features/w_90_90_DS1_rm_bsline_maxRR_u-lbp_MLII.p...
Traceback (most recent call last):
File "C:/Users/qasim/Desktop/jibran/ecg-classification-master/python/run_train_SVM.py", line 54, in
main(multi_mode, 90, 90, do_preprocess, use_weight_class, maxRR, use_RR, norm_RR, compute_morph, oversamp_method, pca_k, feature_selection, do_cross_val, C_value, gamma_value, reduced_DS, leads_flag)
File "C:\Users\qasim\Desktop\jibran\ecg-classification-master\python\train_SVM.py", line 165, in main
maxRR, use_RR, norm_RR, compute_morph, db_path, reduced_DS, leads_flag)
File "C:\Users\qasim\Desktop\jibran\ecg-classification-master\python\load_MITBIH.py", line 434, in load_mit_db
f = open(features_labels_name, 'w')
IOError: [Errno 2] No such file or directory: 'C:/Users/qasim/Desktop/jibran/ecg-classification-master/python/mit_db/features/w_90_90_DS1_rm_bsline_maxRR_u-lbp_MLII.p'

I can't find the cPickle module in project, and I searching cPickle In Project, got the result below:

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

I have trained model, now I want to test it on my own ecg record which is in csv format. I checked all documentation and code files but I have no luck.

While running the run_train_SVM.py, the feature values do get computed, but not sure if they are getting added .
train_SVM.py in main(multi_mode, winL, winR, do_preprocess, use_weight_class, maxRR, use_RR, norm_RR, compute_morph, oversamp_method, pca_k, feature_selection, do_cross_val, C_value, gamma_value, reduced_DS, leads_flag)
195 # scaled: zero mean unit variance ( z-score )
196 scaler = StandardScaler()
--> 197 scaler.fit(tr_features)
198 tr_features_scaled = scaler.transform(tr_features)

Runing train_SVM.py!
Loading MIT BIH arr (DS1) ...
Computing morphological features (DS1) ...
Wavelets ...
labels
writing pickle: /home/mjz/gzy/ecg-classification/python/ECG/mitbih_database/feat ures/w_90_90_DS1_rm_bsline_maxRR_wvlt_MLII.p...
Loading MIT BIH arr (DS2) ...
Computing morphological features (DS2) ...
Wavelets ...
labels
writing pickle: /home/mjz/gzy/ecg-classification/python/ECG/mitbih_database/feat ures/w_90_90_DS2_rm_bsline_maxRR_wvlt_MLII.p...
Traceback (most recent call last):
File "run_train_SVM.py", line 54, in
main(multi_mode, 90, 90, do_preprocess, use_weight_class, maxRR, use_RR, nor m_RR, compute_morph, oversamp_method, pca_k, feature_selection, do_cross_val, C_ value, gamma_value, reduced_DS, leads_flag)
File "/home/mjz/gzy/ecg-classification/python/train_SVM.py", line 195, in main
scaler.fit(tr_features)
File "/home/mjz/anaconda3/lib/python3.5/site-packages/sklearn/preprocessing/da ta.py", line 590, in fit
return self.partial_fit(X, y)
File "/home/mjz/anaconda3/lib/python3.5/site-packages/sklearn/preprocessing/da ta.py", line 612, in partial_fit
warn_on_dtype=True, estimator=self, dtype=FLOAT_DTYPES)
File "/home/mjz/anaconda3/lib/python3.5/site-packages/sklearn/utils/validation .py", line 431, in check_array
context))
ValueError: Found array with 0 sample(s) (shape=(0, 23)) while a minimum of 1 is required by StandardScaler.

I am getting the error '[Errno 2] No such file or directory: '/kaggle/working/features/w_90_90_DS1_rm_bsline_maxRR_u-lbp_MLII.p'' . But after running the run_train_SVM.py . I am getting /kaggle/working/python_mit_rm_bsline_wL_90_wR_90_DS1.p this file created . I don't know why this file is getting created instead of the required one . Anyone pls help !!!

Actually, I want to work on all 180 features rather than extracting few of them(wvlt, HOS, etc)
So is there a way to do that?
Thanks.

I have tried many tricks but DS2 prediction is done all in one class like below:
[ 0 0 44033 0]
[ 0 0 2050 0]
[ 0 0 3220 0]
[ 0 0 388 0]
The prediction made on DS1 is great achieving good accuracy, but seems like a problem in DS2.
I have tried oversampling also but it did not create any difference.
Please help asap, my minor project is pending!

I am trying to clone the repository but I can't seem to pull the python files or the ones from tensorflow.

They all appear deleted when I use the "git status" command and, when I try to restore them, one error message that comes up constantly is this one, also on the title: "fatal: cannot create directory at 'python/aux': Invalid argument".

Don't know if this has to do with anything, but I also found a similar issue online (swcarpentry/DEPRECATED-bc#463) that said "aux" is a reserved word for Windows OS.

Could you maybe check it out?

Thanks in advance!

Morph used: u-lbp
Error: Found array with 0 sample(s) (shape=(0, 59)) while a minimum of 1 is required by StandardScaler.
Morph used: wvlt
Error: Found array with 0 sample(s) (shape=(0, 23)) while a minimum of 1 is required by StandardScaler.