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[Utility & Helpers](/categories/utility) 4. / 5. ankane/libmf ActiveLibrary[Utility & Helpers](/categories/utility) ankane/libmf ============ Large-scale sparse matrix factorization for PHP v0.2.0(1y ago)638521BSD-3-ClausePHPPHP >= 8.1CI passing Since Aug 8Pushed 2mo ago1 watchersCompare [ Source](https://github.com/ankane/libmf-php)[ Packagist](https://packagist.org/packages/ankane/libmf)[ RSS](/packages/ankane-libmf/feed)WikiDiscussions master Synced 1mo ago READMEChangelogDependencies (1)Versions (9)Used By (1) LIBMF PHP ========= [](#libmf-php) [LIBMF](https://github.com/cjlin1/libmf) - large-scale sparse matrix factorization - for PHP Check out [Disco](https://github.com/ankane/disco-php) for higher-level collaborative filtering [![Build Status](https://github.com/ankane/libmf-php/actions/workflows/build.yml/badge.svg)](https://github.com/ankane/libmf-php/actions) Installation ------------ [](#installation) Run: ``` composer require ankane/libmf ``` Add scripts to `composer.json` to download the shared library: ``` "scripts": { "post-install-cmd": "Libmf\\Vendor::check", "post-update-cmd": "Libmf\\Vendor::check" } ``` And run: ``` composer install ``` Getting Started --------------- [](#getting-started) Prep your data in the format `rowIndex, columnIndex, value` ``` $data = new Libmf\Matrix(); $data->push(0, 0, 5.0); $data->push(0, 2, 3.5); $data->push(1, 1, 4.0); ``` Create a model ``` $model = new Libmf\Model(); $model->fit($data); ``` Make predictions ``` $model->predict($rowIndex, $columnIndex); ``` Get the latent factors (these approximate the training matrix) ``` $model->p(); $model->q(); ``` Get the bias (average of all elements in the training matrix) ``` $model->bias(); ``` Save the model to a file ``` $model->save('model.txt'); ``` Load the model from a file ``` $model = Libmf\Model::load('model.txt'); ``` Pass a validation set ``` $model->fit($data, $validSet); ``` Cross-Validation ---------------- [](#cross-validation) Perform cross-validation ``` $model->cv($data); ``` Specify the number of folds ``` $model->cv($data, 5); ``` Parameters ---------- [](#parameters) Pass parameters - default values below ``` use Libmf\Loss; new Libmf\Model( loss: Loss::RealL2, // loss function factors: 8, // number of latent factors threads: 12, // number of threads used bins: 25, // number of bins iterations: 20, // number of iterations lambdaP1: 0, // coefficient of L1-norm regularization on P lambdaP2: 0.1, // coefficient of L2-norm regularization on P lambdaQ1: 0, // coefficient of L1-norm regularization on Q lambdaQ2: 0.1, // coefficient of L2-norm regularization on Q learningRate: 0.1, // learning rate alpha: 1, // importance of negative entries c: 0.0001, // desired value of negative entries nmf: false, // perform non-negative MF (NMF) quiet: false // no outputs to stdout ); ``` ### Loss Functions [](#loss-functions) For real-valued matrix factorization - `Loss::RealL2` - squared error (L2-norm) - `Loss::RealL1` - absolute error (L1-norm) - `Loss::RealKL` - generalized KL-divergence For binary matrix factorization - `Loss::BinaryLog` - logarithmic error - `Loss::BinaryL2` - squared hinge loss - `Loss::BinaryL1` - hinge loss For one-class matrix factorization - `Loss::OneClassRow` - row-oriented pair-wise logarithmic loss - `Loss::OneClassCol` - column-oriented pair-wise logarithmic loss - `Loss::OneClassL2` - squared error (L2-norm) Metrics ------- [](#metrics) Calculate RMSE (for real-valued MF) ``` $model->rmse($data); ``` Calculate MAE (for real-valued MF) ``` $model->mae($data); ``` Calculate generalized KL-divergence (for non-negative real-valued MF) ``` $model->gkl($data); ``` Calculate logarithmic loss (for binary MF) ``` $model->logloss($data); ``` Calculate accuracy (for binary MF) ``` $model->accuracy($data); ``` Calculate MPR (for one-class MF) ``` $model->mpr($data, $transpose); ``` Calculate AUC (for one-class MF) ``` $model->auc($data, $transpose); ``` Example ------- [](#example) Download the [MovieLens 100K dataset](https://grouplens.org/datasets/movielens/100k/) and use: ``` $trainSet = new Libmf\Matrix(); $validSet = new Libmf\Matrix(); if (($handle = fopen('u.data', 'r')) !== false) { $i = 0; while (($row = fgetcsv($handle, separator: "\t")) !== false) { $data = $i < 80000 ? $trainSet : $validSet; $data->push($row[0], $row[1], $row[2]); $i++; } fclose($handle); } $model = new Libmf\Model(factors: 20); $model->fit($trainSet, $validSet); echo $model->rmse($validSet), "\n"; ``` Resources --------- [](#resources) - [LIBMF: A Library for Parallel Matrix Factorization in Shared-memory Systems](https://www.csie.ntu.edu.tw/~cjlin/papers/libmf/libmf_open_source.pdf) History ------- [](#history) View the [changelog](https://github.com/ankane/libmf-php/blob/master/CHANGELOG.md) Contributing ------------ [](#contributing) Everyone is encouraged to help improve this project. Here are a few ways you can help: - [Report bugs](https://github.com/ankane/libmf-php/issues) - Fix bugs and [submit pull requests](https://github.com/ankane/libmf-php/pulls) - Write, clarify, or fix documentation - Suggest or add new features To get started with development: ``` git clone https://github.com/ankane/libmf-php.git cd libmf-php composer install composer test ``` ### Health Score 39 — LowBetter than 86% of packages Maintenance60 Regular maintenance activity Popularity24 Limited adoption so far Community11 Small or concentrated contributor base Maturity51 Maturing project, gaining track record Bus Factor1 Top contributor holds 100% of commits — single point of failure How is this calculated?**Maintenance (25%)** — Last commit recency, latest release date, and issue-to-star ratio. Uses a 2-year decay window. **Popularity (30%)** — Total and monthly downloads, GitHub stars, and forks. Logarithmic scaling prevents top-heavy scores. **Community (15%)** — Contributors, dependents, forks, watchers, and maintainers. Measures real ecosystem engagement. **Maturity (30%)** — Project age, version count, PHP version support, and release stability. ### Release Activity Cadence Every ~133 days Recently: every ~162 days Total 6 Last Release 714d ago PHP version history (2 changes)v0.1.0PHP >= 8.0 v0.2.0PHP >= 8.1 ### Community Maintainers ![](https://avatars.githubusercontent.com/u/220358?v=4)[Andrew Kane](/maintainers/ankane)[@ankane](https://github.com/ankane) --- Top Contributors [![ankane](https://avatars.githubusercontent.com/u/220358?v=4)](https://github.com/ankane "ankane (48 commits)") ### Code Quality TestsPHPUnit ### Embed Badge ![Health badge](/badges/ankane-libmf/health.svg) ``` [![Health](https://phpackages.com/badges/ankane-libmf/health.svg)](https://phpackages.com/packages/ankane-libmf) ``` ### Alternatives [inc2734/wp-breadcrumbs A library for WordPress breadcrumbs. 1543.1k1](/packages/inc2734-wp-breadcrumbs) PHPackages © 2026 [Directory](/)[Categories](/categories)[Trending](/trending)[Changelog](/changelog)[Analyze](/analyze)