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I just put the problem_ Type="binary" becomes "multiclass"
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* Beginning pipeline search *
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Optimizing for Log Loss Multiclass. …
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We have good coverage for what I would call the "default" woodwork types like Double, Boolean, Datetime, NaturalLanguage but how should we handle non-default types that represent more specific data ty…
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Separating out work from https://github.com/alteryx/evalml/issues/2058, https://github.com/alteryx/evalml/pull/2968 tackled the first half of creating a preprocessing pipeline that will encompass all …
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actions_pipeline = make_pipeline_from_data_check_output(problem_type, messages)
data_df, y = actions_pipeline.fit(data_df, target)
#################################################
Error Message:…
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Looks like the default action right now is "impute" for regression
https://github.com/alteryx/evalml/blob/main/evalml/data_checks/invalid_target_data_check.py#L247
I think a) one of the actions sh…
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https://github.com/alteryx/evalml/pull/2846 added vowpal wabbit estimators to EvalML, but they are currently not used in AutoMLSearch.
This would require performance testing and determining a good …
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- As a user, I wish I had an easy way to tell the difference between two Woodwork TableSchemas.
When passing around Woodwork dataframes, it is easy to lose track of some of the woodwork types, lik…
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#### Code Sample, a copy-pastable example to reproduce your bug.
```python
import pandas as pd
from evalml.pipelines.components import ExponentialSmoothingRegressor
from evalml.preprocessing…
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Follow up on https://github.com/alteryx/evalml/pull/3182 based on @freddyaboulton's comment:
I think we can improve this implementation. Right now we do two scans of the data to determine the highl…
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Hello,
I'm training a Time series regression model and I have a problem when predicting.
![image](https://user-images.githubusercontent.com/18369529/118267833-e7c17a00-b4bc-11eb-9993-d5aa250f6b5…