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@stdlib/ml

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Machine learning algorithms.

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/** * @license Apache-2.0 * * Copyright (c) 2018 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ 'use strict'; // MODULES // var dot = require( './dot.js' ); // MAIN // /** * Computes the squared cosine distance between two data points. * * @private * @param {NonNegativeInteger} N - number of elements * @param {NumericArray} X - strided array * @param {PositiveInteger} strideX - stride * @param {NonNegativeInteger} offsetX - index offset * @param {NumericArray} Y - strided array * @param {PositiveInteger} strideY - stride * @param {NonNegativeInteger} offsetY - index offset * @returns {number} squared cosine distance */ function squaredCosine( N, X, strideX, offsetX, Y, strideY, offsetY ) { // TODO: consider moving to an "extended" BLAS package var d = 1.0 - dot( N, X, strideX, offsetX, Y, strideY, offsetY ); return d * d; } // EXPORTS // module.exports = squaredCosine;