FIx small typo

[louisguitton]

What changes are proposed in this pull request?

Fixing small typo in the warning message.
Before the change:

2021/09/03 18:53:45 WARNING mlflow.sklearn.utils: precision_score failed. The metric test_gold_precision_scorewill not be recorded. Metric error: '<' not supported between instances of 'float' and 'str'
2021/09/03 18:53:45 WARNING mlflow.sklearn.utils: recall_score failed. The metric test_gold_recall_scorewill not be recorded. Metric error: '<' not supported between instances of 'float' and 'str'
2021/09/03 18:53:45 WARNING mlflow.sklearn.utils: f1_score failed. The metric test_gold_f1_scorewill not be recorded. Metric error: '<' not supported between instances of 'float' and 'str'
2021/09/03 18:53:45 WARNING mlflow.sklearn.utils: accuracy_score failed. The metric test_gold_accuracy_scorewill not be recorded. Metric error: '<' not supported between instances of 'float' and 'str'

How is this patch tested?

from mlflow.sklearn.utils import _log_warning_for_metrics
from sklearn.metrics import precision_score

# given
func_name = "test_gold_precision_score"
func_call = precision_score
err = Exception("'<' not supported between instances of 'float' and 'str'"

# when
_log_warning_for_metrics(func_name, func_call, err)

# then
# visually assert that the words are correctly spaced out

Release Notes

Is this a user-facing change?

• No. You can skip the rest of this section.
• Yes. Give a description of this change to be included in the release notes for MLflow users.

(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 logging
• area/build: Build and test infrastructure for MLflow
• area/docs: MLflow documentation pages
• area/examples: Example code
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/models: MLmodel format, model serialization/deserialization, flavors
• area/projects: MLproject format, project running backends
• area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• area/server-infra: MLflow Tracking server backend
• area/tracking: Tracking Service, tracking client APIs, autologging

Interface

• area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
• area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
• area/windows: Windows support

Language

• language/r: R APIs and clients
• language/java: Java APIs and clients
• language/new: Proposals for new client languages

Integrations

• integrations/azure: Azure and Azure ML integrations
• integrations/sagemaker: SageMaker integrations
• integrations/databricks: Databricks integrations

How should the PR be classified in the release notes? Choose one:

• rn/breaking-change - The PR will be mentioned in the "Breaking Changes" section
• rn/none - No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" section
• rn/feature - A new user-facing feature worth mentioning in the release notes
• rn/bug-fix - A user-facing bug fix worth mentioning in the release notes
• rn/documentation - A user-facing documentation change worth mentioning in the release notes

[github-actions]

@louisguitton Thanks for the contribution! The DCO check failed. Please sign off your commits by following the instructions here: https://github.com/mlflow/mlflow/runs/3508740632. See https://github.com/mlflow/mlflow/blob/master/CONTRIBUTING.rst#sign-your-work for more details.

[harupy]

lgtm