Add Time Series Baseline Regression Components and Pipelines

[jeremyliweishih]

Fixes #1482.

• Add regressor
• Add pipeline
• Add to automl

[codecov]

Codecov Report

Merging #1496 (924a2c1) into main (f88a866) will increase coverage by 0.1%.
The diff coverage is 100.0%.

@@            Coverage Diff            @@
##             main    #1496     +/-   ##
=========================================
+ Coverage   100.0%   100.0%   +0.1%     
=========================================
  Files         223      227      +4     
  Lines       15316    15483    +167     
=========================================
+ Hits        15309    15476    +167     
  Misses          7        7             

Impacted Files	Coverage Δ
evalml/pipelines/components/__init__.py	100.0% <ø> (ø)
evalml/pipelines/components/estimators/__init__.py	100.0% <ø> (ø)
.../tests/pipeline_tests/test_time_series_pipeline.py	100.0% <ø> (ø)
evalml/automl/automl_search.py	99.7% <100.0%> (+0.1%)	⬆️
evalml/pipelines/__init__.py	100.0% <100.0%> (ø)
...lines/components/estimators/regressors/__init__.py	100.0% <100.0%> (ø)
...ators/regressors/time_series_baseline_regressor.py	100.0% <100.0%> (ø)
evalml/pipelines/regression/__init__.py	100.0% <100.0%> (ø)
...ines/regression/time_series_baseline_regression.py	100.0% <100.0%> (ø)
...valml/pipelines/time_series_regression_pipeline.py	100.0% <100.0%> (ø)
... and 12 more

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[freddyaboulton]

@jeremyliweishih Thank you so much! This is great.

I think this is almost good to merge but I think we need to tweak the implementation of the regressor a bit to ensure the predictions and targets are offset by the right amount by the time we get to pipeline score.

[freddyaboulton]

I don't think we should do any shifting here and predict should basically be a no-op that returns the y that is passed in.

The score method in TimeSeriesRegressionPipeline will shift the target by -gap which will ensure the target is gap time periods ahead of the prediction. Right now, with this shift they would be offset by gap + 1 which I don't think is intended. Let's say the user has dates October 1-8 and the gap is 3. I think the desired pairs of prediction and target dates should be:

Prediction Date	Target Date
2020-10-01	2020-10-04
2020-10-02	2020-10-05
2020-10-03	2020-10-06
2020-10-04	2020-10-07
2020-10-05	2020-10-08

We need to be mindful of the gap=0 case, cause we should shift by 1 in this predict method to avoid perfect overlap in the pipeline score method.

[jeremyliweishih]

@freddyaboulton got it! will make the changes.

[freddyaboulton]

I think we should use the problem configuration parameters passed by the user to ensure the shifting between targets and predictions is accurate.

[jeremyliweishih]

right, thanks!

updated!

[freddyaboulton]

@jeremyliweishih I think this is great! Thank you so much for helping on this. Before merging, I suggest we add a test that verifies that the predictions and targets are offset by the right amount in the baseline pipeline (just cause that's a pretty big deal and I want to make sure we have something in place to guard against regressions in future refactorings). I think we should also add the baseline pipeline and estimator to the api ref?

Other than that, I left some comments that don't need to be resolved before merging!

[freddyaboulton]

Can you please add a test that verifies that the predictions and targets are offset by the right amount in score for both the gap=0 and gap > 0 cases? This can be similar to test_score_drop_nans in test_time_series_pipeline.