Calculating Feature Importance of Time Series Data2019 Community Moderator ElectionHow to deal with time series which change in seasonality or other patterns?Statistical distances for time series of distributionsTime series prediction using ARIMA vs LSTMScaling multiple time series dataExploratory analysis and feature engineering for time till failure prediction using sensor data of enginesContinuously predicting eventsRNNs for time series prediction - what configurations would make senseTime series binary classificaiton with labelling issuesFully endogenous models for predicting multivariate time seriesHow to solve a classification problem when the independent variables/covariates/feature vectors form a time series?
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Calculating Feature Importance of Time Series Data
2019 Community Moderator ElectionHow to deal with time series which change in seasonality or other patterns?Statistical distances for time series of distributionsTime series prediction using ARIMA vs LSTMScaling multiple time series dataExploratory analysis and feature engineering for time till failure prediction using sensor data of enginesContinuously predicting eventsRNNs for time series prediction - what configurations would make senseTime series binary classificaiton with labelling issuesFully endogenous models for predicting multivariate time seriesHow to solve a classification problem when the independent variables/covariates/feature vectors form a time series?
$begingroup$
I am new to time-series modeling, and I was wondering what the standard way of quantifying feature importances are in a time-series setting? What types of models allow for the greatest interpretation of the feature space?
I am looking for something, which does not necessarily function like the Random Forest Regressor's feature importance call, but provides a similar insight.
time-series feature-extraction
asked Mar 27 at 16:39
studyingforphysicsrightnowstudyingforphysicsrightnow
31
$endgroup$
add a comment |
$begingroup$
I am new to time-series modeling, and I was wondering what the standard way of quantifying feature importances are in a time-series setting? What types of models allow for the greatest interpretation of the feature space?
I am looking for something, which does not necessarily function like the Random Forest Regressor's feature importance call, but provides a similar insight.
time-series feature-extraction
asked Mar 27 at 16:39
studyingforphysicsrightnowstudyingforphysicsrightnow
31
$endgroup$
add a comment |
$begingroup$
I am new to time-series modeling, and I was wondering what the standard way of quantifying feature importances are in a time-series setting? What types of models allow for the greatest interpretation of the feature space?
I am looking for something, which does not necessarily function like the Random Forest Regressor's feature importance call, but provides a similar insight.
time-series feature-extraction
asked Mar 27 at 16:39
studyingforphysicsrightnowstudyingforphysicsrightnow
31
$endgroup$
I am new to time-series modeling, and I was wondering what the standard way of quantifying feature importances are in a time-series setting? What types of models allow for the greatest interpretation of the feature space?
I am looking for something, which does not necessarily function like the Random Forest Regressor's feature importance call, but provides a similar insight.
time-series feature-extraction
time-series feature-extraction
asked Mar 27 at 16:39
studyingforphysicsrightnowstudyingforphysicsrightnow
31
asked Mar 27 at 16:39
studyingforphysicsrightnowstudyingforphysicsrightnow
31
asked Mar 27 at 16:39
studyingforphysicsrightnowstudyingforphysicsrightnow
31
asked Mar 27 at 16:39
studyingforphysicsrightnowstudyingforphysicsrightnow
31
asked Mar 27 at 16:39
studyingforphysicsrightnowstudyingforphysicsrightnow
31
31
add a comment |
add a comment |
1 Answer
1
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oldest
votes
$begingroup$
For time series data,
- Sensitivity analysis can help with overall Importance of a feature. For example, is "Day of the week" a good feature for stock price forecasting. LIME is one approach that can help. Details : https://arxiv.org/abs/1606.05386 . One simple way is to mask each feature and check the impact on model's performance.
- Auto-corelation and Seasonality removal (Details in tutorial at end of the answer)
- SHAP : (SHapley Additive exPlanations) is good at identifying features that impact output with lag (https://medium.com/datadriveninvestor/time-step-wise-feature-importance-in-deep-learning-using-shap-e1c46a655455)
End to end example :
https://machinelearningmastery.com/feature-selection-time-series-forecasting-python/
answered Mar 28 at 4:16
Shamit VermaShamit Verma
1,4291214
$endgroup$
add a comment |
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1 Answer
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1 Answer
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votes
$begingroup$
For time series data,
- Sensitivity analysis can help with overall Importance of a feature. For example, is "Day of the week" a good feature for stock price forecasting. LIME is one approach that can help. Details : https://arxiv.org/abs/1606.05386 . One simple way is to mask each feature and check the impact on model's performance.
- Auto-corelation and Seasonality removal (Details in tutorial at end of the answer)
- SHAP : (SHapley Additive exPlanations) is good at identifying features that impact output with lag (https://medium.com/datadriveninvestor/time-step-wise-feature-importance-in-deep-learning-using-shap-e1c46a655455)
End to end example :
https://machinelearningmastery.com/feature-selection-time-series-forecasting-python/
answered Mar 28 at 4:16
Shamit VermaShamit Verma
1,4291214
$endgroup$
add a comment |
$begingroup$
For time series data,
- Sensitivity analysis can help with overall Importance of a feature. For example, is "Day of the week" a good feature for stock price forecasting. LIME is one approach that can help. Details : https://arxiv.org/abs/1606.05386 . One simple way is to mask each feature and check the impact on model's performance.
- Auto-corelation and Seasonality removal (Details in tutorial at end of the answer)
- SHAP : (SHapley Additive exPlanations) is good at identifying features that impact output with lag (https://medium.com/datadriveninvestor/time-step-wise-feature-importance-in-deep-learning-using-shap-e1c46a655455)
End to end example :
https://machinelearningmastery.com/feature-selection-time-series-forecasting-python/
answered Mar 28 at 4:16
Shamit VermaShamit Verma
1,4291214
$endgroup$
add a comment |
$begingroup$
For time series data,
- Sensitivity analysis can help with overall Importance of a feature. For example, is "Day of the week" a good feature for stock price forecasting. LIME is one approach that can help. Details : https://arxiv.org/abs/1606.05386 . One simple way is to mask each feature and check the impact on model's performance.
- Auto-corelation and Seasonality removal (Details in tutorial at end of the answer)
- SHAP : (SHapley Additive exPlanations) is good at identifying features that impact output with lag (https://medium.com/datadriveninvestor/time-step-wise-feature-importance-in-deep-learning-using-shap-e1c46a655455)
End to end example :
https://machinelearningmastery.com/feature-selection-time-series-forecasting-python/
answered Mar 28 at 4:16
Shamit VermaShamit Verma
1,4291214
$endgroup$
For time series data,
- Sensitivity analysis can help with overall Importance of a feature. For example, is "Day of the week" a good feature for stock price forecasting. LIME is one approach that can help. Details : https://arxiv.org/abs/1606.05386 . One simple way is to mask each feature and check the impact on model's performance.
- Auto-corelation and Seasonality removal (Details in tutorial at end of the answer)
- SHAP : (SHapley Additive exPlanations) is good at identifying features that impact output with lag (https://medium.com/datadriveninvestor/time-step-wise-feature-importance-in-deep-learning-using-shap-e1c46a655455)
End to end example :
https://machinelearningmastery.com/feature-selection-time-series-forecasting-python/
answered Mar 28 at 4:16
Shamit VermaShamit Verma
1,4291214
answered Mar 28 at 4:16
Shamit VermaShamit Verma
1,4291214
answered Mar 28 at 4:16
Shamit VermaShamit Verma
1,4291214
answered Mar 28 at 4:16
Shamit VermaShamit Verma
1,4291214
1,4291214
add a comment |
add a comment |
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