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ML Classification

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The ML Classification component uses the Snowflake Classification machine learning (ML) function to sort data into different classes using patterns detected in training data. The component requires that you have already created the trained model on your warehouse.

The component supports both binary classification and multi-class classification.

According to the Snowflake documentation:

Common use cases of classification include customer churn prediction, credit card fraud detection, and spam detection.

Note

Read Snowflake's documentation for details about limitations, costs, preparation, and more.


Properties

Database = drop-down

The Snowflake database that the classification model resides in. The special value, [Environment Default], will use the database defined in the environment. Read Databases, Tables and Views - Overview to learn more.


Schema = drop-down

The Snowflake schema that the classification model resides in. The special value, [Environment Default], will use the schema defined in the environment. Read Database, Schema, and Share DDL to learn more.


Model = drop-down

The model to use. Read the Snowflake documentation to learn more about creating and using models.


On Error = drop-down

  • ABORT: Abort the entire prediction operation if any rows result in an error.
  • SKIP: Skip any rows that result in an error. The error is shown instead of the results for that row.

Prediction Column Name = string

The name of the column where the model's output will be situated.


Class Column Name = string

The name of the column where the classifications will appear. The predicted class is extracted from the model output for the user.

For example, if your data's classification will be either "true" or "false", specifying classification in this parameter will generate a column that explicitly lists "true" and "false" values per row classified.


Include Input Columns = boolean

  • Yes: Includes both the column names of the input data and the output columns Prediction Column Name and Class Column Name.
  • No: Only includes the Prediction Column Name and Class Column Name columns.

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