ModelTaskParams

ModelTaskParams defines task-specific parameters that control how models are evaluated and monitored within Fiddler. Different model types (classification, regression, ranking) require different parameters to properly compute metrics and perform analysis. These parameters are essential for accurate metric computation, proper baseline establishment, and meaningful performance monitoring across different model types and use cases.

Examples

Configuration for binary classification:

binary_params = ModelTaskParams(
    binary_classification_threshold=0.5,
    target_class_order=["negative", "positive"]
)

Configuration for multi-class classification with class weights:

multiclass_params = ModelTaskParams(
    target_class_order=["class_a", "class_b", "class_c"],
    class_weights=[0.3, 0.5, 0.2],
    weighted_ref_histograms=True
)

Configuration for ranking models:

ranking_params = ModelTaskParams(
    group_by="query_id",
    top_k=10,
    target_class_order=["not_relevant", "relevant", "highly_relevant"]
)

Configuration for imbalanced datasets:

imbalanced_params = ModelTaskParams(
    binary_classification_threshold=0.3,
    class_weights=[0.1, 0.9],
    weighted_ref_histograms=True
)

Attributes

float | None

Threshold for labels

List | None

Order of target classes

str | None

Query/session id column for ranking models

int | None

Top k results to consider when computing ranking metrics

List[float] | None

Weight of each classes

bool | None

Whether baseline histograms must be weighted or not while drift metrics

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Fiddler Google ADK SDK

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Fiddler OTel JS SDK

Fiddler LangGraph JS SDK

Fiddler LangChain JS SDK

Examples

Attributes

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Examples

Attributes