Sanjay Kumar comments

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Sanjay Kumar

TypeError: unhashable type: 'slice'

It is not running on regression problem, how can I run it on regression model?

NeuroKit Warning: ecg_hrv(): Correlation Dimension. Error: NeuroKit warning: complexity_entropy_multiscale(): Signal might be to short to compute SampEn for scale factors > 0. Setting max_scale_factor to 0.

my dataset is ptb ecg database. you can check it on https://www.physionet.org/physiobank/database/ptbdb/

NeuroKit Warning: ecg_hrv(): Correlation Dimension. Error: NeuroKit warning: complexity_entropy_multiscale(): Signal might be to short to compute SampEn for scale factors > 0. Setting max_scale_factor to 0.

firstly you read the description. I want to know how to convert these twelve columns (i, ii, iii, avr, avl, avf, v1, v2, v3, v4, v5, v6) into features for...

NeuroKit Warning: ecg_hrv(): Correlation Dimension. Error: NeuroKit warning: complexity_entropy_multiscale(): Signal might be to short to compute SampEn for scale factors > 0. Setting max_scale_factor to 0.

@DominiqueMakowski

NeuroKit Warning: ecg_hrv(): Correlation Dimension. Error: NeuroKit warning: complexity_entropy_multiscale(): Signal might be to short to compute SampEn for scale factors > 0. Setting max_scale_factor to 0.

![screenshot from 2018-04-14 18-23-07](https://user-images.githubusercontent.com/18687010/38768721-7102e66a-4011-11e8-8c86-9e0f5313a16b.png)

NeuroKit Warning: ecg_hrv(): Correlation Dimension. Error: NeuroKit warning: complexity_entropy_multiscale(): Signal might be to short to compute SampEn for scale factors > 0. Setting max_scale_factor to 0.

this is how my one data column which I (i) as I mentioned above looks like

NeuroKit Warning: ecg_hrv(): Correlation Dimension. Error: NeuroKit warning: complexity_entropy_multiscale(): Signal might be to short to compute SampEn for scale factors > 0. Setting max_scale_factor to 0.

@gattia

NeuroKit Warning: ecg_hrv(): Correlation Dimension. Error: NeuroKit warning: complexity_entropy_multiscale(): Signal might be to short to compute SampEn for scale factors > 0. Setting max_scale_factor to 0.

thanks @DominiqueMakowski it is really useful, but tell me ecg_preprocess() and bio_process() works alike in my case?

NeuroKit Warning: ecg_hrv(): Correlation Dimension. Error: NeuroKit warning: complexity_entropy_multiscale(): Signal might be to short to compute SampEn for scale factors > 0. Setting max_scale_factor to 0.

as I have already mentioned you that I am using dataset of PTB ecg dataset, and your library also inculcates it. But ecg_preprocess() also fails on some signals giving error...

NeuroKit Warning: ecg_hrv(): Correlation Dimension. Error: NeuroKit warning: complexity_entropy_multiscale(): Signal might be to short to compute SampEn for scale factors > 0. Setting max_scale_factor to 0.

If I only process LEAD 1 (i in my data), then would it give features which ('T_Waves', 'Cardiac_Cycles', 'P_Waves', 'Q_Waves', 'HRV', 'R_Peaks') helps me in classification of heart disease class.