@arizeai/phoenix-evals
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A library for running evaluations for AI use cases
23 lines • 981 B
TypeScript
import type { EvaluatorBase } from "../core/EvaluatorBase.js";
import type { ClassificationExample, PrecisionRecallFScoreOptions } from "./classificationMetrics.js";
export type F1EvaluatorOptions = Omit<PrecisionRecallFScoreOptions, "beta">;
/**
* Creates a code evaluator that computes the F1 score: the harmonic mean of
* precision and recall.
*
* Supports binary classification (via `positiveLabel`, or auto-detected when
* labels are the numeric set `{0, 1}`) and multi-class classification (via
* the `average` strategy).
*
* @example
* ```typescript
* const f1 = createF1Evaluator();
* const result = await f1.evaluate({
* expected: ["cat", "dog", "cat", "bird"],
* output: ["cat", "cat", "cat", "bird"],
* });
* // { score: 0.6 }
* ```
*/
export declare function createF1Evaluator<RecordType extends ClassificationExample = ClassificationExample>(options?: F1EvaluatorOptions): EvaluatorBase<RecordType>;
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