Pipeline v2.0 (refactor) #108
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* Added imputer * Clean up imputer * added onehot and standard scaler * Need fix selectfrommodel and validating * Add selectfrommodel * Cleanup and added basic init test * lint
Codecov Report
@@ Coverage Diff @@
## master #108 +/- ##
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+ Coverage 95.75% 96.64% +0.88%
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Files 58 89 +31
Lines 1531 2233 +702
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+ Hits 1466 2158 +692
- Misses 65 75 +10
Continue to review full report at Codecov.
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Fixed SelectFromModel
…nto pipeline_v2
…nto pipeline_v2
kmax12
suggested changes
Oct 28, 2019
| from evalml.problem_types import ProblemTypes | ||
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| class RFRegressionPipeline(PipelineBase): | ||
| """Random Forest Pipeline for regression""" | ||
| name = "Random Forest w/ imputation" | ||
| name = "Random Forest Regressor w/ One Hot Encoder + Simple Imputer + Select From Model" | ||
| model_type = ModelTypes.RANDOM_FOREST |
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can we automatically determine the model type since it's annotated on the component?
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Likewise to the auto generated names: we can auto determine but would require changes to Autobase so we think its best to hold off until then.
| from evalml.problem_types import ProblemTypes | ||
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| class RFRegressionPipeline(PipelineBase): | ||
| """Random Forest Pipeline for regression""" | ||
| name = "Random Forest w/ imputation" | ||
| name = "Random Forest Regressor w/ One Hot Encoder + Simple Imputer + Select From Model" | ||
| model_type = ModelTypes.RANDOM_FOREST | ||
| problem_types = [ProblemTypes.REGRESSION] |
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can we automatically determine the problem types since it's annotated on the component?
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Note: refactor feature_importances and self.input_feature_names code :) Edit: Addressed. |
* cleanup components utils * Switch to category_encoder and cleanup RF Select * add feature_importance to estimator * More switching to CE * Move parameters to class attributes and make test * lint * Separate changelog test * Text cleanup
* wip: addressing comments * feature names? * adding fix for no estimator in generate_name * fixing test * addressing more comments on feature_importance * feature_importances fixed and cleaned :) * oops, missed merge conflict * change of name * minor cleanup * adding basic test for two feature selectors and adding default components in DEFAULT_COMPONENTS * adding tests for retaining feature names in input_feature_names
kmax12
suggested changes
Nov 4, 2019
evalml/pipelines/components/transformers/feature_selection/feature_selector.py
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kmax12
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Nov 4, 2019
kmax12
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Nov 4, 2019
evalml/pipelines/components/transformers/feature_selection/feature_selector.py
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WIP: laying down the basis for #95