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Documentation Index

Fetch the complete documentation index at: https://arize-ax.mintlify.dev/docs/llms.txt

Use this file to discover all available pages before exploring further.

View source on Github Arize enum to specify your model type represented in the platform and validate applicable performance metrics.

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Model Types

from arize.utils.types import ModelTypes
Specify a model_type when logging a prediction for the first time for a new model.

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Method

list_types() View Source Returns a list of all model types. 
ModelTypes.list_types()
Use CaseSDK ModelTypeDescription
RegressionModelTypes.REGRESSIONRegression models predict continuous values
Binary ClassificationModelType.BINARY_CLASSIFICATIONBinary classification models predict only two categorical values, typically represented as 0 or 1
RankingModelType.RANKINGRanking models predict the relative ordering of a set of items based on their features
Multi ClassModelType.MULTI_CLASSMulticlass models predict multiple categorical values
Natural Language Processing (NLP)ModelType.SCORE_CATEGORICALNLP models are categorical models specifically designed to work with text data and perform various tasks (i.e. sentiment analysis and language translation)
Computer Vision (CV)ModelType.SCORE_CATEGORICALCV models are categorical models specifically designed to work with visual data and perform various tasks (i.e. object detection and image classification)
Large Language Models (LLMs)ModelTypes.GENERATIVE_LLMModels that use vast amounts of data to generate human-like language and perform a wide range of natural language processing tasks
Object DetectionModelTypes.OBJECT_DETECTIONObject detection models identify and locate objects within images or videos by assigning them specific bounding boxes

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Code Example

response = arize_client.log(
  (model_id = "sample-binary-classification-model"),
  ...(model_type = ModelTypes.BINARY_CLASSIFICATION)
);

response = arize_client.log(
  (model_id = "sample-regression-model"),
  ...(model_type = ModelTypes.REGRESSION)
);

response = arize_client.log(
  (model_id = "sample-ranking-model"),
  ...(model_type = ModelTypes.RANKING)
);