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Installation\r\n> `npm install --save @types/skmeans`\r\n\r\n# Summary\r\nThis package contains type definitions for skmeans (https://github.com/solzimer/skmeans).\r\n\r\n# Details\r\nFiles were exported from https://github.com/DefinitelyTyped/DefinitelyTyped/tree/master/types/skmeans.\r\n## [index.d.ts](https://github.com/DefinitelyTyped/DefinitelyTyped/tree/master/types/skmeans/index.d.ts)\r\n````ts\r\ntype CentroidValues<TPoint extends number | number[]> = TPoint[] | \"kmrand\" | \"kmpp\";\n\ninterface TestResult<TPoint> {\n    idx: number;\n    centroid: TPoint;\n}\n\ninterface DataResult<TPoint extends number | number[]> {\n    it: number;\n    k: number;\n    centroids: TPoint[];\n    idxs: number[];\n    test: (x: TPoint, distance?: (x: TPoint, y: TPoint) => number) => TestResult<TPoint>;\n}\n\n/**\n * Calculates unidimiensional and multidimensional k-means clustering on data.\n *\n * @param data Unidimiensional or multidimensional array of values to be clustered.\n * @param k Number of clusters.\n * @param centroids Initial centroid values.\n * @param iterations Maximum number of iterations. If not provided, it will be set to 10000.\n * @param distance Custom distance function. Takes two points as arguments and returns a scalar number.\n */\ndeclare function skmeans<TPoint extends number | number[]>(\n    data: TPoint[],\n    k: number,\n    centroids?: CentroidValues<TPoint> | null,\n    iterations?: number | null,\n    distance?: (x: TPoint, y: TPoint) => number | null,\n): DataResult<TPoint>;\n\nexport = skmeans;\n\r\n````\r\n\r\n### Additional Details\r\n * Last updated: Thu, 30 Jan 2025 11:32:28 GMT\r\n * Dependencies: none\r\n\r\n# Credits\r\nThese definitions were written by .","users":{}}