LIBFFM - field-aware factorization machines - in Rust
LIBFFM Rust is available as a Rust library and a command line tool.
Add this line to your application’s Cargo.toml under [dependencies]:
libffm = "0.2"Prep your data in LIBFFM format
0 0:0:1 1:1:1
1 0:2:1 1:3:1Train a model
let model = libffm::Model::train("train.ffm").unwrap();Use a validation set and early stopping to prevent overfitting
let model = libffm::Model::params()
.auto_stop(true)
.train_eval("train.ffm", "valid.ffm")
.unwrap();Make predictions
let (predictions, loss) = model.predict("test.ffm").unwrap();Save the model to a file
model.save("model.bin").unwrap();Load a model from a file
let model = libffm::Model::load("model.bin").unwrap();let model = libffm::Model::params()
.learning_rate(0.2) // learning rate
.lambda(0.00002) // regularization parameter
.iterations(15) // number of iterations
.factors(4) // number of latent factors
.quiet(false) // quiet mode (no output)
.normalization(true) // use instance-wise normalization
.auto_stop(false) // stop at the iteration that achieves the best validation loss
.on_disk(false) // on-disk training
.train("train.ffm"); // train or train_evalRun:
cargo install libffm --features cliPrep your data in LIBFFM format
0 0:0:1 1:1:1
1 0:2:1 1:3:1Train a model
ffm-train train.ffm model.binUse a validation set and early stopping to prevent overfitting
ffm-train -p valid.ffm --auto-stop train.ffm model.binMake predictions
ffm-predict test.ffm model.bin output.txtFLAGS:
--auto-stop Stop at the iteration that achieves the best validation loss (must be used with -p)
--in-memory Enable in-memory training
--no-norm Disable instance-wise normalization
--quiet Quiet mode (no output)
OPTIONS:
-r <eta> Set learning rate [default: 0.2]
-k <factor> Set number of latent factors [default: 4]
-t <iteration> Set number of iterations [default: 15]
-l <lambda> Set regularization parameter [default: 0.00002]
-s <nr-threads> Set number of threads [default: 1]
-p <va-path> Set path to the validation setThis library was ported from the LIBFFM C++ library and is available under the same license.
View the changelog
Everyone is encouraged to help improve this project. Here are a few ways you can help:
- Report bugs
- Fix bugs and submit pull requests
- Write, clarify, or fix documentation
- Suggest or add new features
To get started with development:
git clone https://github.com/ankane/libffm-rust.git
cd libffm-rust
cargo test
cargo run --bin ffm-train --features cli
cargo run --bin ffm-predict --features cli