Hyperparameter Tuning for Time Series Causal Impact Analysis in R | Machine Learning
CausalImpactpackage created by Google estimates the impact of an intervention on a time series. In this tutorial, we will talk about how to tune the hyperparameters of the time series causal impact model using the R package CausalImpact.
⏰ Timecodes ⏰
0:00 - Intro
0:14 - Step 1: Install and Import R Libraries
1:04 - Step 2: Create Dataset
2:59 - Step 3: Set Pre and Post Periods
3:53 - Step 4: Causal Impact on Time Series with Default Hyperparameters
5:06 - Step 5: Hyperparameter Tuning for niter
5:30 - Step 6: Hyperparameter Tuning for standardize.data
5:57 - Step 7: Hyperparameter Tuning for prior.level.sd
7:11 - Step 8: Hyperparameter Tuning for nseasons
8:14 - Step 9: Hyperparameter Tuning for season.duration
9:16 - Step 10: Hyperparameter Tuning for dynamic.regression
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🎞️ Time Series Causal Impact Analysis in R: • Time Series Causal Impact Analysis in R | ...
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