Sep, 2023 Release We are releasing Temporian, a library for preprocessing and feature engineering of temporal data.
Sep, 2023 News Start of our Discord server.
Aug, 2023 Publication Yggdrasil Decision Forests: A Fast and Extensible Decision Forests Library at KDD’2023 (extended version)
Jul, 2023 Release TensorFlow Decision Forests 1.5.0
Jul, 2023 Release Yggdrasil Decision Forests 1.5.0
Sep, 2022 Release Go API to run Yggdrasil Decision Forest models.
Jul, 2022 Publication Generative Trees: Adversarial and Copycat at ICML’2022
Random Forest, Gradient Boosted Trees, CART, and variations such as Dart, Extremely randomized trees.
Classification, regression, ranking and uplifting.
Model evaluation e.g. accuracy, auc, roc, auuc, pr-auc, confidence boundaries, ndgc.
Model analysis e.g. pdp, cep, variable importance, model plotting, structure analysis.
Native support for numerical, categorical, boolean, categorical-set (e.g. text) features.
Native support for missing values.
State of the art tree learning features e.g. oblique split, honest tree, hessian score, global tree optimization.
Automatic hyper-parameter tuning.
Fast model inference e.g. vpred, quick-scorer extended.
See the feature list for more details.
About TensorFlow Decision Forests#
TensorFlow Decision Forests is a library for training, evaluating, interpreting, and inferring decision forest models in TensorFlow. TensorFlow Decision Forests uses Yggdrasil Decision Forests for model training. TensorFlow Decision Forests models are compatible with Yggdrasil Decision Forests.