Comments (5)
have you transformed your dataframe or dataset to array, e.g. with np.array(media_data_train)?
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I did like this, on the tutorial. it is an array but still doesn't let me use the Scalers:
from lightweight_mmm.
it is an array, and is float32, it should be in good shape already. WHich dataset threw an error? target? media? or others?
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As you can see below the target_train caused errors. The Scalers & fit_transofrm of media_data_train and costs worked.
And this is how target_train looks like:
from lightweight_mmm.
Hmmmm.... I know you have checked it already, but would there be any chance that your target_train has nan, null, zero, or different data dtype?
Do you mind to provide your notebook, and data for further investigation? I am not sure if there is any pm function in github.
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Related Issues (20)
- limitations in the use of extra features HOT 4
- Anyway to save mmm.print_summary()? HOT 1
- Hierarchical Partially Pooled Media
- media_priors HOT 1
- Get contribution from predict
- How can I calibrate my predicted ROI in the MMM with my geolift result ? HOT 3
- How can I run kind of gridsearch to find the best custom priors for a hill_adstock or carryover model ?
- How can I input future media_data_test for optimization in upcoming periods? HOT 1
- How can channel-wise optimized conversions be obtained?
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- Divergences and n_eff
- Outliers and influential points
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