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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 format = require( '@stdlib/string/format' ); // MAIN // /** * Returns a function to retrieve the current learning rate. * * @private * @param {string} type - string denoting the learning rate to use. Can be `constant`, `pegasos` or `basic`. * @param {PositiveNumber} eta0 - constant learning rate * @param {NonNegativeNumber} lambda - regularization parameter * @throws {Error} first argument must be `basic`, `constant` or `pegasos` * @returns {Function} getEta function */ function closure( type, eta0, lambda ) { var iter; var ret; iter = 1; switch ( type ) { case 'basic': // Default case: 'basic' ret = getEtaBasic; break; case 'constant': ret = getEtaConstant; break; case 'pegasos': ret = getEtaPegasos; break; default: throw new Error( format( 'invalid option. `%s` option must be one of the following: "%s". Option: `%s`.', 'learningRate', [ 'basic', 'constant', 'pegasos' ].join( '", "' ), type ) ); } return ret; /** * Returns the basic learning rate. * * @private * @returns {number} learning rate */ function getEtaBasic() { var eta = 1000.0 / ( iter + 1000.0 ); iter += 1; return eta; } /** * Returns the constant learning rate. * * @private * @returns {number} learning rate */ function getEtaConstant() { iter += 1; return eta0; } /** * Returns the Pegasos learning rate. * * @private * @returns {number} learning rate */ function getEtaPegasos() { var eta = 1.0 / ( lambda * iter ); iter += 1; return eta; } } // EXPORTS // module.exports = closure;