For IterativeAlgorithm, put time series algorithms first#3407
For IterativeAlgorithm, put time series algorithms first#3407freddyaboulton merged 15 commits intomainfrom
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@@ Coverage Diff @@
## main #3407 +/- ##
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- Coverage 99.7% 99.7% -0.0%
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Files 332 332
Lines 32445 32510 +65
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+ Hits 32316 32380 +64
- Misses 129 130 +1
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| self.data_splitter = self.data_splitter or default_data_splitter | ||
| self.pipeline_parameters = pipeline_parameters or {} | ||
| self.custom_hyperparameters = custom_hyperparameters or {} | ||
| # Fitting takes a long time if the data is too wide or long. |
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Justification here:
| if user_arima_hyperparams and not self.custom_hyperparameters[ | ||
| ARIMARegressor.name | ||
| ].get("use_covariates"): | ||
| self.custom_hyperparameters[ARIMARegressor.name].update( |
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Setting this up with custom hyperparameters is the best way I think. It lets users override our heuristic if they don't mind waiting.
| extras_require = { | ||
| 'update_checker': ['alteryx-open-src-update-checker >= 2.0.0'], | ||
| 'prophet': ['cmdstan-builder == 0.0.8'] | ||
| 'prophet': ['prophet-prebuilt == 1.0.2'] |
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Using pre-built wheels to speed up installation.
| .tolist() | ||
| ) | ||
| if is_using_windows: | ||
| expected_order = [ |
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This is covered because windows test pass but we don't measure coverage for windows.
freddyaboulton
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Awesome Freddy, this looks great. You're going to make people very happy :)
| run: | | ||
| source test_python/bin/activate | ||
| pip install cmdstan-builder==0.0.8 | ||
| pip install prophet-prebuilt==1.0.2 |
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booo, I wanted prophet-freddy
| "XGBoost Regressor", | ||
| ] | ||
| else: | ||
| expected_order = [ |
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Do we care about order? Probably a nit but I'd think checking that ESR, Prophet and ARIMA are simply in the list of the first few is what we care about. Feel free to ignore though. Just don't want to be changing this test over and over :)
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The good news is that adding a new model family won't break this test unless we explicitly change the _ESTIMATOR_FAMILY_ORDER
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Pull Request Description
Move time series estimators to the front of the queue for the iterative algorithm based on user feedback.
After creating the pull request: in order to pass the release_notes_updated check you will need to update the "Future Release" section of
docs/source/release_notes.rstto include this pull request by adding :pr:123.