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10. Prediction
Predictions can take the form of scores, labels, and values depending on model type

Overview

Score Models

  • Prediction Score: Score Likelihood of the event
  • Prediction Label: Based on the score and a threshold, the classification label of this event

Regression Models

  • Prediction Value: The numeric value that the prediction is for regression models
Predictions (outputs of a model) can take the form of scores, labels, and values depending on model type

Code Example

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schema = Schema(
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prediction_id_column_name="prediction_id",
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timestamp_column_name="prediction_ts",
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prediction_label_column_name="PREDICTION",
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prediction_score_column_name="PREDICTION_SCORE",
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actual_label_column_name="ACTUAL",
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actual_score_column_name="ACTUAL_SCORE",
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feature_column_names=["MERCHANT_TYPE", "ENTRY_MODE", "STATE", "MEAN_AMOUNT", "STD_AMOUNT", "TX_AMOUNT"],
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)
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# Log the dataframe with the schema mapping
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response = arize_client.log(
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model_id="sample-model-1",
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model_version= "v1",
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model_type=ModelTypes.SCORE_CATEGORICAL,
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environment=Environments.PRODUCTION,
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dataframe=test_dataframe,
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schema=schema,
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Last modified 3mo ago
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