Snowflake ML release notes¶

See Snowflake ML: End-to-End Machine Learning for documentation.

Version 1.1.2 (2023-12-18)¶

New features and updates¶

Model development updates:

• Implemented precision_score metric in SQL.

Bug fixes¶

• Fixed an issue where stack trace was being hidden by telemetry.

Model development fixes:

• Inferring model signatures no longer materializes the full dataframe in memory.

Version 1.1.1 (2023-12-6)¶

New features and updates¶

• Designated Snowpark ML Modeling API as Generally Available.
• New passthrough_col parameter in the Modeling API allows you to exclude specific columns, like index columns, during training or inference when not explicitly specifying input_cols.

Bug fixes¶

• Model development fixes:
  • confusion_matrix provided incorrect results when the row number could not be divided by the batch size.

Version 1.1.0 (2023-12-1)¶

New features and updates¶

• GridSearchCV and RandomizedSearchCV execution is now distributed on multi-node warehouses.

Bug fixes¶

• Model development fixes:
  • Columns were being excluded if their normalized names did not match the names specified in output_columns in OrdinalEncoder and LabelEncoder. Output columns no longer need to be valid Snowflake identifiers.

Version 1.0.12 (2023-11-15)¶

New features and updates¶

• None

Bug fixes¶

• Model development fixes:
  • Increased the column capacity of OrdinalEncoder.

Version 1.0.11 (2023-10-28)¶

New features and updates¶

• Add support for kneighbors.
• Support DecimalType as a data type.

Bug fixes¶

• Model development fixes:
  • Fix support for XGBoost and LightGBM models using SKLearn Grid Search and Randomized Search model selectors.
  • Fix metrics compatibility with Snowpark DataFrames that use Snowflake identifiers

Version 1.0.10 (2023-10-15)¶

New features and updates¶

• precision_score, recall_score, f1_score, fbeta_score, precision_recall_fscore_support, mean_absolute_error, mean_squared_error, and mean_absolute_percentage_error metric calculations are now distributed.

Bug fixes¶

• Model development fixes:
  • Fix UTF-8 decoding errors when using modeling modules on Windows.
  • Fix alias definitions causing SnowparkSQLUnexpectedAliasException in inference.

Version 1.0.9 (2023-09-28)¶

New features and updates¶

• Calculation of log_loss metric is now distributed.

Bug fixes¶

• Model development fixes:
  • Building images no longer fails with some Docker setups.
  • Embedding local ML library no longer fails when the library is imported by zipimport.
  • Update incorrect documentation about platform argument in the deploy function.

Version 1.0.8 (2023-09-15)¶

New features and updates¶

• None

Bug fixes¶

• Model development fixes:
  • Ordinal encoder can be used with mixed input column types.
  • Fix an issue when the sklearn default value is np.nan.

Version 1.0.7 (2023-09-05)¶

New features and updates¶

• Allow disabling telemetry.

Bug fixes¶

• Model development fixes:
  • Fix an error related to pandas.io.json.json_normalizer.

Version 1.0.6 (2023-09-01)¶

New features and updates¶

• Model development: Size of metrics result can exceed previous 8MB limit.

Bug fixes¶

• Model development fixes:
  • Fixed a bug when using simple imputer with NumPy >= 1.25.
  • Fixed a bug when inferring the type of label columns.

Version 1.0.5 (2023-08-17)¶

This release contains internal changes only.

Version 1.0.4 (2023-07-28)¶

New features and updates¶

• Model development: Input dataframes can now be joined against data loaded from staged files.
• Model development: Added support for non-English languages.

Bug fixes¶

• None

Version 1.0.3 (2023-07-14)¶

This release contains internal changes only.

Version 1.0.2 (2023-06-22)¶

New features and updates¶

• Model development: Added metrics:
  • d2_absolute_error_score
  • d2_pinball_score
  • explained_variance_score
  • mean_absolute_error
  • mean_absolute_percentage_error
  • mean_squared_error

Bug fixes¶

Model development: accuracy_score now works when given label column names that are lists of single values.

Version 1.0.1 (2023-06-16)¶

Behavior changes¶

• Model development: Changed Metrics APIs to follow scikit-learn metrics modules:
  • accuracy_score, confusion_matrix, precision_recall_fscore_support, and precision_score methods move to metrics.classification.

New features and updates¶

• Model development: Added metrics:
  • f1_score
  • fbeta_score
  • recall_score
  • roc_auc_score
  • roc_curve
  • log_loss
  • precision_recall_curve

Version 1.0.0 (2023-06-09)¶

Initial public preview release.