deepbox/metrics
Classification Metrics
Classification scores, threshold curves, reports, and confusion-matrix utilities.
Evaluation
accuracy
export declare function accuracy(yTrue: Tensor, yPred: Tensor): number;
Calculates the accuracy classification score.
averagePrecisionScore
export declare function averagePrecisionScore(yTrue: Tensor, yScore: Tensor): number;
Average precision score.
balancedAccuracyScore
export declare function balancedAccuracyScore(yTrue: Tensor, yPred: Tensor): number;
Balanced accuracy score.
classificationReport
export declare function classificationReport(yTrue: Tensor, yPred: Tensor): string;
Generates a text classification report showing main classification metrics.
cohenKappaScore
export declare function cohenKappaScore(yTrue: Tensor, yPred: Tensor): number;
Cohen's kappa score.
confusionMatrix
export declare function confusionMatrix(yTrue: Tensor, yPred: Tensor): Tensor;
Computes the confusion matrix to evaluate classification accuracy.
f1Score
export declare function f1Score(yTrue: Tensor, yPred: Tensor, average: { average: "binary" | "micro" | "macro" | "weighted"; }): number;
f1Score is exported by deepbox/metrics.
fbetaScore
export declare function fbetaScore(yTrue: Tensor, yPred: Tensor, beta: number, average: null): number[];
fbetaScore is exported by deepbox/metrics.
hammingLoss
export declare function hammingLoss(yTrue: Tensor, yPred: Tensor): number;
Hamming loss.
jaccardScore
export declare function jaccardScore(yTrue: Tensor, yPred: Tensor): number;
Jaccard similarity score (Intersection over Union).
logLoss
export declare function logLoss(yTrue: Tensor, yPred: Tensor): number;
Log loss (logistic loss, cross-entropy loss).
matthewsCorrcoef
export declare function matthewsCorrcoef(yTrue: Tensor, yPred: Tensor): number;
Matthews correlation coefficient (MCC).
precision
export declare function precision(yTrue: Tensor, yPred: Tensor, average: null): number[];
precision is exported by deepbox/metrics.
precisionRecallCurve
export declare function precisionRecallCurve(yTrue: Tensor, yScore: Tensor): [Tensor, Tensor, Tensor];
Precision-Recall curve.
recall
export declare function recall(yTrue: Tensor, yPred: Tensor, average: null): number[];
recall is exported by deepbox/metrics.
rocAucScore
export declare function rocAucScore(yTrue: Tensor, yScore: Tensor): number;
Area Under ROC Curve (AUC-ROC).
rocCurve
export declare function rocCurve(yTrue: Tensor, yScore: Tensor): [Tensor, Tensor, Tensor];
ROC curve data.
metrics-classification.ts
import { accuracy, classificationReport, confusionMatrix, f1Score, rocAucScore,} from "deepbox/metrics";import { tensor } from "deepbox/ndarray";const yTrue = tensor([0, 1, 1, 0, 1]);const yPred = tensor([0, 1, 0, 0, 1]);const yScore = tensor([0.1, 0.8, 0.4, 0.2, 0.9]);console.log(accuracy(yTrue, yPred));console.log(f1Score(yTrue, yPred));console.log(rocAucScore(yTrue, yScore));console.log(confusionMatrix(yTrue, yPred).toString());console.log(classificationReport(yTrue, yPred));