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    Interface PredictiveStudioCreateScoringProcessInput

    Input for PredictiveStudio.CreateScoringProcess.

    interface PredictiveStudioCreateScoringProcessInput {
        modelId: string;
        name?: string;
        outputField?: string;
        primaryKeyField?: string;
        scope: { all?: boolean; filter?: string; listId?: string; viewId?: string };
        targetEntityName: string;
        valueKind?: "score" | "class";
    }
    Index

    Properties

    modelId name? outputField? primaryKeyField? scope targetEntityName valueKind?

    Properties

    modelId: string

    Id of the MJ: ML Models row the created Record Process scores with.

    name?: string

    Optional Record Process name; a descriptive default is generated when omitted.

    outputField?: string

    Optional. The target-entity column to write the prediction into (e.g. RenewalScore). When supplied → write-back mode: each run writes the prediction into that column AND a MJ: ML Model Scoring Bindings lineage row (Mode='OnDemand') is created. When omitted → generic output, no binding: predictions are recorded in the process run history (MJ: Process Run Details) only, with no write-back column and no scoring binding.

    primaryKeyField?: string

    Primary-key field on the target entity the model joins on (defaults to ID).

    scope: { all?: boolean; filter?: string; listId?: string; viewId?: string }

    The records a run scores. Mirrors the Record Set Processing scope shapes (Filter / View / List). Populate EXACTLY ONE selector; all is the whole-entity shortcut ("score everyone"), expressed under the hood as a Filter with the all-rows predicate (1=1).

    Type Declaration

    • Optionalall?: boolean

      Score the WHOLE target entity ("score everyone"); mutually exclusive with the others.

    • Optionalfilter?: string

      A SQL filter over the target entity selecting the rows to score.

    • OptionallistId?: string

      A Lists id whose member rows are scored.

    • OptionalviewId?: string

      A User Views id whose rows are scored.

    targetEntityName: string

    The entity whose rows are scored (e.g. Memberships).

    valueKind?: "score" | "class"

    Which prediction value the write-back lands in outputField — the numeric 'score' (probability / regression value — the default) or the predicted 'class' label (classification). Ignored in generic mode (no outputField).

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