@ai-on-browser/data-analysis-models
Version:
Data analysis model package without any dependencies
31 lines (30 loc) • 1.1 kB
TypeScript
/**
* Inverse distance weighting
*/
export default class InverseDistanceWeighting {
/**
* @param {number} [k] Number of neighborhoods
* @param {number} [p] Power parameter
* @param {'euclid' | 'manhattan' | 'chebyshev' | 'minkowski' | function (number[], number[]): number} [metric] Metric name
*/
constructor(k?: number, p?: number, metric?: "euclid" | "manhattan" | "chebyshev" | "minkowski" | ((arg0: number[], arg1: number[]) => number));
_k: number;
_p: number;
_metric: "euclid" | "manhattan" | "chebyshev" | "minkowski" | ((arg0: number[], arg1: number[]) => number);
_d: (a: any, b: any) => any;
_near_points(data: any): any[];
/**
* Fit model.
* @param {Array<Array<number>>} x Training data
* @param {number[]} y Target values
*/
fit(x: Array<Array<number>>, y: number[]): void;
_x: number[][];
_y: number[];
/**
* Returns predicted values.
* @param {Array<Array<number>>} data Sample data
* @returns {number[]} Predicted values
*/
predict(data: Array<Array<number>>): number[];
}