Releases: paritybit-ai/XFL
Releases · paritybit-ai/XFL
Release v1.4.1
- Feat:
- Operators:
- Horizontal: xgboost;
- Operators:
Release v1.4.0
-
Feat:
- Operators:
- Vertical:poisson_regression;
- Horizontal: poisson_regression, kmeans, gcn_mol, vgg_jax;
- New horizontal template for Jax;
- Operators:
-
Improvement:
- The vertical operator parameters are simplified, and the assist_trainer parameter does not need to be configured before training;
Release v1.3.0
- Feat:
- Operators:
- Vertical:linear_regression, sampler;
- Horizontal: bert, densenet, vgg, woe_iv;
- Local: data_split, data_statistic, feature_preprocess;
- New horizontal templates for TensorFlow, PaddlePaddle;
- Vertical XGBoost supports category features and offline inference, the output model file changes to json format;
- Vertical K-Means supports new initial method kmeans++;
- Operators:
- Improvement:
- The vertical operator parameters are simplified, and the assist_trainer parameter does not need to be configured before training;