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* @license Apache-2.0
*
* Copyright (c) 2026 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 isPositiveInteger = require( '@stdlib/assert/is-positive-integer' );
var isObject = require( '@stdlib/assert/is-plain-object' );
var hasOwnProp = require( '@stdlib/assert/has-own-property' );
var format = require( '@stdlib/string/format' );
// MAIN //
/**
* Serializes an SGD trainer params object as a formatted string.
*
* ## Notes
*
* - Example output:
*
* ```text
*
* Stochastic Gradient Descent
*
* penalty: l2
* learning rate: constant
* loss function: hinge
* lambda: 2.5000
* eta0: 0.0100
* fit intercept: true
* intercept: 0.0000
* max iterations: 1000
*
* ```
*
* @param {Object} params - SGD trainer params object
* @param {Options} [opts] - options object
* @param {PositiveInteger} [opts.digits=4] - number of digits to display after decimal points
* @throws {TypeError} options argument must be an object
* @throws {TypeError} must provide valid options
* @returns {string} serialized params
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var params = {
* 'penaltyParams': new Float64Array( [ 2.5, 0.0 ] ),
* 'learningRateParams': new Float64Array( [ 0.01, 0.0 ] ),
* 'lossFunctionParams': new Float64Array( [ 0.0 ] ),
* 'intercept': 0.0,
* 'maxIter': 1000,
* 'penalty': 'l2',
* 'learningRate': 'constant',
* 'lossFunction': 'hinge',
* 'fitIntercept': true,
* 'method': 'Stochastic Gradient Descent'
* };
*
* var str = toString( params );
* // returns <string>
*/
function toString( params, opts ) { // eslint-disable-line stdlib/no-redeclare
var fitIntercept;
var dgts;
var out;
dgts = 4;
if ( arguments.length > 1 ) {
if ( !isObject( opts ) ) {
throw new TypeError( format( 'invalid argument. Must provide an object. Value: `%s`.', opts ) );
}
if ( hasOwnProp( opts, 'digits' ) ) {
if ( !isPositiveInteger( opts.digits ) ) {
throw new TypeError( format( 'invalid option. `%s` option must be a positive integer. Option: `%s`.', 'digits', opts.digits ) );
}
dgts = opts.digits;
}
}
fitIntercept = 'false';
if ( params.fitIntercept === true ) {
fitIntercept = 'true';
}
out = [
'',
params.method,
'',
format( ' penalty: %s', params.penalty ),
format( ' learning rate: %s', params.learningRate ),
format( ' loss function: %s', params.lossFunction )
];
if ( params.penalty !== 'none' ) {
out.push( format( ' lambda: %0.'+dgts+'f', params.penaltyParams[ 0 ] ) );
if ( params.penalty === 'elasticnet' ) {
out.push( format( ' l1 ratio: %0.'+dgts+'f', params.penaltyParams[ 1 ] ) );
}
}
if ( params.learningRate === 'constant' ) {
out.push( format( ' eta0: %0.'+dgts+'f', params.learningRateParams[ 0 ] ) );
}
else if ( params.learningRate === 'invscaling' ) {
out.push( format( ' eta0: %0.'+dgts+'f', params.learningRateParams[ 0 ] ) );
out.push( format( ' powerT: %0.'+dgts+'f', params.learningRateParams[ 1 ] ) );
} else if ( params.learningRate === 'pegasos' && params.penalty === 'none' ) {
out.push( format( ' lambda: %0.'+dgts+'f', params.learningRateParams[ 0 ] ) );
}
if ( params.lossFunction === 'epsilon-insensitive' || params.lossFunction === 'squared-epsilon-insensitive' ) {
out.push( format( ' epsilon: %0.'+dgts+'f', params.lossFunctionParams[ 0 ] ) );
}
if ( params.lossFunction === 'huber' ) {
out.push( format( ' huber threshold: %0.'+dgts+'f', params.lossFunctionParams[ 0 ] ) );
}
out.push( format( ' fit intercept: %s', fitIntercept ) );
if ( params.fitIntercept === true ) {
out.push( format( ' intercept: %0.'+dgts+'f', params.intercept ) );
}
out.push( format( ' max iterations: %d', params.maxIter ) );
out.push( '' );
return out.join( '\n' );
}
// EXPORTS //
module.exports = toString;
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