srendle/libfm

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1487 stars · 408 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

libFM is a C++ library implementing factorization machines, a model that combines feature engineering with factorization models to estimate interactions between categorical variables. It supports SGD, ALS, and MCMC (Bayesian inference) optimization and ships as a command-line tool.

Use cases

• train factorization machine models on categorical feature data
• build recommendation and click-through-rate prediction models
• predict ratings from sparse user-item interaction data
• run Bayesian inference with MCMC for factorization machines
• model pairwise feature interactions without manual feature engineering

When to choose

• you need factorization machines with SGD, ALS, or MCMC training
• your data has large sparse categorical feature spaces
• you want a proven, well-cited implementation for CTR or recommender tasks

When to avoid

• you need a Python-native or GPU-accelerated ML workflow
• you require active development, recent releases, or community support
• you need deep learning or neural recommender models

Facets

library · maturity maintenance

machine-learning math machine-learning data-science cpp cli factorization-machines sgd als mcmc recommendation categorical-features algorithms linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="srendle/libfm")