Evaluate Api examples#5186
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dbczumar
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@WeichenXu123 Can we change the directory name to examples/evaluation/? Can we also add a README file to this folder with a short explanation of the feature and an explanation of what each of the example Python scripts does?
LGTM after that!
Signed-off-by: Weichen Xu <weichen.xu@databricks.com>
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| print(f"metrics:\n{result.metrics}") | ||
| print(f"artifacts:\n{result.artifacts}") |
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This line's output looks like:
{'roc_curve_plot': <mlflow.models.evaluation.artifacts.ImageEvaluationArtifact object at 0x7f5d98244950>,
'precision_recall_curve_plot': <mlflow.models.evaluation.artifacts.ImageEvaluationArtifact object at 0x7f5d982890d0>,
'lift_curve_plot': <mlflow.models.evaluation.artifacts.ImageEvaluationArtifact object at 0x7f5d985bc250>,
'confusion_matrix': <mlflow.models.evaluation.artifacts.ImageEvaluationArtifact object at 0x7f5d9826bc10>,
'shap_beeswarm_plot': <mlflow.models.evaluation.artifacts.ImageEvaluationArtifact object at 0x7f5d98123fd0>,
'shap_summary_plot': <mlflow.models.evaluation.artifacts.ImageEvaluationArtifact object at 0x7f5d2c18fd50>,
'shap_feature_importance_plot': <mlflow.models.evaluation.artifacts.ImageEvaluationArtifact object at 0x7f5d96eb1990>}
We might want to implement __str__ for EvaluationArtifact for better string representation (e.g. <EvaluationArtifact file_name.png>).
cc @dbczumar
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We can do this in follow-up updates.
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I add a __repr__ for evaluation artifact , format is like ImageEvaluationArtifact(uri='...')
Signed-off-by: Weichen Xu <weichen.xu@databricks.com>
What changes are proposed in this pull request?
Evaluate Api examples
How is this patch tested?
N/A
Does this PR change the documentation?
ci/circleci: build_doccheck. If it's successful, proceed to thenext step, otherwise fix it.
Detailson the right to open the job page of CircleCI.Artifactstab.docs/build/html/index.html.Release Notes
Is this a user-facing change?
(Details in 1-2 sentences. You can just refer to another PR with a description if this PR is part of a larger change.)
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts: Artifact stores and artifact loggingarea/build: Build and test infrastructure for MLflowarea/docs: MLflow documentation pagesarea/examples: Example codearea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models: MLmodel format, model serialization/deserialization, flavorsarea/projects: MLproject format, project running backendsarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra: MLflow Tracking server backendarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows: Windows supportLanguage
language/r: R APIs and clientslanguage/java: Java APIs and clientslanguage/new: Proposals for new client languagesIntegrations
integrations/azure: Azure and Azure ML integrationsintegrations/sagemaker: SageMaker integrationsintegrations/databricks: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/feature- A new user-facing feature worth mentioning in the release notesrn/bug-fix- A user-facing bug fix worth mentioning in the release notesrn/documentation- A user-facing documentation change worth mentioning in the release notes