KiGB
Machine learning framework
An open-source software framework that integrates human advice into gradient boosting decision trees for improved performance in machine learning tasks.
Knowledge-intensive Gradient Boosting: A unified framework for learning gradient boosted decision trees for regression and classification tasks while leveraging human advice for achieving better performance.
8 stars
3 watching
4 forks
Language: Python
last commit: over 2 years ago
Linked from 1 awesome list
Related projects:
Repository | Description | Stars |
---|---|---|
kingfengji/mgbdt | An implementation of a gradient boosting decision tree model | 102 |
microsoft/0xdeca10b | A framework for hosting and training machine learning models on a blockchain, enabling secure sharing and prediction without requiring users to pay for data or model updates. | 559 |
serengil/chefboost | A Python library providing a lightweight framework for building decision trees with categorical feature support | 463 |
stanfordmlgroup/ngboost | A Python library implementing a machine learning boosting framework with probabilistic prediction capabilities | 1,663 |
melisgl/mgl | A Common Lisp machine learning library that supports neural networks, Boltzmann machines, and other algorithms. | 593 |
anitan0925/resfgb | An implementation of functional gradient boosting based on residual network perception for non-linear classification problems. | 28 |
tqchen/xgboost | An optimized distributed gradient boosting library for machine learning | 572 |
somnibyte/mlkit | A framework for implementing machine learning algorithms in Swift to make it easier for developers to incorporate ML into their projects. | 152 |
tensorflow/decision-forests | Provides tools and APIs for training, serving, and interpreting decision forest models in TensorFlow. | 666 |
dmlc/xgboost.jl | A Julia package implementing a distributed gradient boosting framework with efficient linear model solver and tree learning algorithms. | 288 |
gianlucabertani/machinelearning | A machine learning framework for native code on Macs with support for neural networks and natural language processing. | 37 |
fff-rs/juice | A machine learning framework designed to be extensible and agnostic, with support for multiple backends and linear algebra libraries. | 1,114 |
jinlow/forust | A package implementing a lightweight gradient boosted decision tree algorithm | 68 |
pouyamghari/pof-mkl | An implementation of an online federated learning algorithm with multiple kernels for personalized machine learning | 0 |
kubeflow/katib | An automated machine learning system that supports hyperparameter tuning and neural architecture search on Kubernetes. | 1,521 |