deepbox/datasets
Synthetic Generators
Structured dataset generators for classification, regression, manifold, low-rank, and clustering benchmarks.
Synthetic data
makeBiclusters
export declare function makeBiclusters(options?: { shape?: [number, number]; nClusters?: number; noise?: number; randomState?: number; }): [Tensor, Tensor, Tensor];
Generate a bicluster dataset.
makeBlobs
export declare function makeBlobs(options?: { nSamples?: number; nFeatures?: number; centers?: number | number[][]; clusterStd?: number; randomState?: number; shuffle?: boolean; }): [Tensor, Tensor];
Generate isotropic Gaussian blobs for clustering.
makeCheckerboard
export declare function makeCheckerboard(options?: { shape?: [number, number]; nClusters?: [number, number]; noise?: number; randomState?: number; }): [Tensor, Tensor, Tensor];
Generate a checkerboard dataset.
makeCircles
export declare function makeCircles(options?: { nSamples?: number; noise?: number; factor?: number; randomState?: number; shuffle?: boolean; }): [Tensor, Tensor];
Generate a large circle containing a smaller circle in 2D.
makeClassification
export declare function makeClassification(options?: { nSamples?: number; nFeatures?: number; nInformative?: number; nRedundant?: number; nClasses?: number; flipY?: number; randomState?: number; }): [Tensor, Tensor];
Generate a random n-class classification dataset.
makeFriedman1
export declare function makeFriedman1(options?: { nSamples?: number; nFeatures?: number; noise?: number; randomState?: number; }): [Tensor, Tensor];
Generate the Friedman #1 regression dataset.
makeFriedman2
export declare function makeFriedman2(options?: { nSamples?: number; noise?: number; randomState?: number; }): [Tensor, Tensor];
Generate the Friedman #2 regression dataset.
makeFriedman3
export declare function makeFriedman3(options?: { nSamples?: number; noise?: number; randomState?: number; }): [Tensor, Tensor];
Generate the Friedman #3 regression dataset.
makeGaussianQuantiles
export declare function makeGaussianQuantiles(options?: { nSamples?: number; nFeatures?: number; nClasses?: number; randomState?: number; }): [Tensor, Tensor];
Generate a dataset with classes separated by concentric Gaussian quantile shells.
makeLowRankMatrix
export declare function makeLowRankMatrix(options?: { nSamples?: number; nFeatures?: number; effectiveRank?: number; randomState?: number; }): Tensor;
Generate a low-rank matrix with optional noise.
makeMoons
export declare function makeMoons(options?: { nSamples?: number; noise?: number; randomState?: number; shuffle?: boolean; }): [Tensor, Tensor];
Generate two interleaving half-circle (moons) dataset.
makeRegression
export declare function makeRegression(options?: { nSamples?: number; nFeatures?: number; noise?: number; randomState?: number; }): [Tensor, Tensor];
Generate a random regression dataset.
makeSCurve
export declare function makeSCurve(options?: { nSamples?: number; noise?: number; randomState?: number; }): [Tensor, Tensor];
Generate an S-curve dataset (3D manifold).
makeSPDMatrix
export declare function makeSPDMatrix(options?: { nDim?: number; randomState?: number; }): Tensor;
Generate a random symmetric positive-definite matrix.
makeSwissRoll
export declare function makeSwissRoll(options?: { nSamples?: number; noise?: number; randomState?: number; }): [Tensor, Tensor];
Generate a Swiss Roll dataset (3D manifold).
datasets-synthetic.ts
import { makeBlobs, makeClassification, makeMoons, makeRegression, makeSwissRoll,} from "deepbox/datasets";console.log(makeClassification({ nSamples: 100, nFeatures: 4 }));console.log(makeRegression({ nSamples: 100, nFeatures: 4 }));console.log(makeBlobs({ nSamples: 100, centers: 3 }));console.log(makeMoons({ nSamples: 100 }));console.log(makeSwissRoll({ nSamples: 100 }));