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Forum Posts

colinsorensen
by New Contributor III
  • 1332 Views
  • 3 replies
  • 1 kudos

"All trials either failed or did not return results to hyperopt." AutoML is not working on a fairly simple classification problem.

First the exploratory notebook fails, though when I run it manually it works just fine.After that, the AutoML notebook eventually fails without completing any trials. I get this: Tried to attach usage logger `pyspark.databricks.pandas.usage_logger`, ...

  • 1332 Views
  • 3 replies
  • 1 kudos
Latest Reply
colinsorensen
New Contributor III
  • 1 kudos

Ultimately this problem magically resolved itself. I think I updated the cluster or something.

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Qwetroman
by New Contributor
  • 752 Views
  • 1 replies
  • 0 kudos

AutoML runs fail after 5 seconds

Hi everyoneI am exploring automl, and I met a strange problem - after I launch a classification experiment on my personal newly created cluster (screenshot attached) it successfully performs data exploration, but after that, all runs fail after appro...

  • 752 Views
  • 1 replies
  • 0 kudos
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swethaNandan
New Contributor III
  • 0 kudos

Hi Qwetroman,we can see the following error message in the notebook - ExecutionTimeoutError: Execution timed out before any trials could be successfully run. Please increase the timeout for AutoML to run some trials.What's the size of the dataset? St...

  • 0 kudos
anonturtle
by New Contributor
  • 611 Views
  • 1 replies
  • 0 kudos

How does automl classify which feature is numeric or categorical?

When running automl on its UI, it classifies a feature "local_convenience_store" as both a numeric and categorical column. This affects the result as for numeric columns a scaler is used while in a categorical column it is one hot encoded. For contex...

  • 611 Views
  • 1 replies
  • 0 kudos
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Anonymous
Not applicable
  • 0 kudos

@hr then​ :The approach taken by AutoML to classify features as numeric or categorical depends on the specific AutoML framework or library being used, as different implementations may use different methods or heuristics to make this determination.In ...

  • 0 kudos
RRO
by Contributor
  • 908 Views
  • 1 replies
  • 3 kudos

AutoML forecasting with monthly data?

ARIMA and FBProphet have the capability to forecast monthly data. When using AutoML (via the API or the UI) it seems like it is not possible to have a monthly freq (e.g. 'MS').Is there a way / workaround to make it work with monthly data or is it pla...

  • 908 Views
  • 1 replies
  • 3 kudos
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Mateusz_Lomansk
New Contributor II
  • 3 kudos

It is possible to use AutoML to forecast monthly data, but it may require some additional steps or adjustments.One approach is to resample the monthly data to a lower frequency such as weekly or daily, and then use AutoML to forecast at that lower fr...

  • 3 kudos
Christine
by Contributor
  • 4223 Views
  • 7 replies
  • 3 kudos

Resolved! autoML' is not found when using databricks.automl with runtime 112.ML (and runtime 10.4 LTS ML).

I have tried to set up a autoML experiment with runtime 11.2ML and data from a delta table. However I receive the error "ModuleNotFoundError: No module named 'databricks.automl'" and "AutoML not available: Use Databricks Runtime 8.3 ML or above." tho...

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  • 4223 Views
  • 7 replies
  • 3 kudos
Latest Reply
Christine
Contributor
  • 3 kudos

I deleted the cluster and created a new with runtime 9.1 LTS ML which solved the problem.

  • 3 kudos
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Hayley
by New Contributor III
  • 2210 Views
  • 2 replies
  • 2 kudos

What is the best way to do EDA in Databricks?

Are there example notebooks to quickstart the exploratory data analysis?

  • 2210 Views
  • 2 replies
  • 2 kudos
Latest Reply
Hayley
New Contributor III
  • 2 kudos

A quick way to start exploratory data analysis is to use the EDA notebook that is created when you use Databricks AutoML. Then you can use the notebook generated as is, or as a starting point for modeling. You’ll need a cluster with Databricks Runtim...

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