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bin+lib tangram_tree

Tangram makes it easy for programmers to train, deploy, and monitor machine learning models

4 releases (breaking)

0.7.0 Aug 17, 2021
0.6.0 Jul 19, 2021
0.5.0 Jul 2, 2021
0.4.0 Jun 25, 2021

#15 in #ruby-on-rails

Download history 43/week @ 2022-01-20 81/week @ 2022-01-27 63/week @ 2022-02-03 30/week @ 2022-02-10 32/week @ 2022-02-17 33/week @ 2022-02-24 59/week @ 2022-03-03 41/week @ 2022-03-10 65/week @ 2022-03-17 71/week @ 2022-03-24 28/week @ 2022-03-31 27/week @ 2022-04-07 15/week @ 2022-04-14 5/week @ 2022-04-21 50/week @ 2022-04-28 42/week @ 2022-05-05

112 downloads per month
Used in 3 crates (2 directly)

MIT license

425KB
10K SLoC

Tangram Tree

This crate is documented using rustdoc. View the docs for the most recent version at https://docs.rs/tangram_tree or run cargo doc -p tangram_tree --open in the root of this repository.


lib.rs:

This crate implements machine learning models for regression and classification using ensembles of decision trees. It has many similarities to LightGBM, XGBoost, and others, but is written in pure Rust.

For an example of regression, see benchmarks/boston.rs.rs. For an example of binary classification, see benchmarks/heart_disease.rs. For an example of multiclass classification, see benchmarks/iris.rs`.

Dependencies

~13MB
~242K SLoC