Reverse Dependencies of xgboost

The following projects have a declared dependency on xgboost:

• a2grunnerp — A2G Runner for Local Workflow
• Academic-Forecasting-System — no summary
• accutuning-helpers — no summary
• acv-dev — ACV is a library that provides robust and accurate explanations for machine learning models or data
• acv-exp — ACV is a library that provides robust and accurate explanations for machine learning models or data
• adbench — Python package of ADBench
• adcirc-rom — Add a short description here!
• adval — Adversarial validation for train-test datasets
• adversarial-robustness-toolbox — Toolbox for adversarial machine learning.
• advertion — A tiny framework to perform adversarial validation of your training and test data.
• ageml — AgeML is a Python package for Age Modelling with Machine Learning made easy.
• agh-vqis — A Python wrapper for 18 image quality indicators.
• aglite-test.tabular — AutoML for Image, Text, and Tabular Data
• aimodelshare-nightly — Deploy locally saved machine learning models to a live rest API and web-dashboard. Share it with the world via modelshare.org
• aisdc — Tools for the statistical disclosure control of machine learning models
• aisimplekit — Simple lib for various machine learning and AI tasks.
• akerbp.models — Machine Learning Models for Petrophysics
• akimous — An intelligent Python IDE
• ale-uy — Tool to perform data cleaning, modeling and visualization in a simple way.
• algo-auto-ml — AutoML library for binary classification and regression tasks
• AlgoMaster — The Regression class simplifies regression analysis by providing a convenient and flexible approach for model training, evaluation, and hyperparameter tuning.The Classifier class streamlines classification tasks by offering a well-organized framework for model selection, hyperparameter tuning,
• all-models — A package that contains all regression and classification models
• allestm — Predicting various structural features of transmembrane proteins.
• alpha-automl — Alpha-AutoML: NYU's AutoML System
• Alpha-Mind — no summary
• alphaml — Build a CLETE Binary Classification Model
• AMLBID — Transparent and Auto-explainable AutoML
• AMLpp — Wrapper for ml library
• amorf — A framework for multi-output regression in Python
• ampel-hu-astro — Astronomy units for the Ampel system from HU-Berlin
• Amplo — Fully automated end to end machine learning pipeline
• anai-opensource — Automated ML
• analogainas — AnalogAINAS: A modular and extensible Analog-aware Neural Architecture Search (NAS) library.
• apollo-lunar — A Python SDK/CLI for Lunar API
• aq-geometric — Geometric deep learning on air quality data.
• ArambhML — An Auto ML framework that solves Classification Tasks
• Astras — Package for Classification and Regression
• astrodust — A library for predicting the distribution of dust particles in protoplanetary disks
• AstroSubtractor — Machine learning classifier
• atlantic — Atlantic is an automated preprocessing framework for Supervised Machine Learning
• atml — Automation Toolkit for Machine Learning
• atom-ml — A Python package for fast exploration of machine learning pipelines
• AttentionMOI — A Denoised Multi-omics Integration Framework for Cancer Subtype Classification and Survival Prediction.
• atts — Train_test splitter with adversarial validation
• auger.ai.predict — Auger ML predict python and command line interface
• auto-aiml — Creates a best predictive regression/classification model
• Auto-ML-C — A small example package
• auto-ml-cl — Auto machine learning with scikit-learn and TensorFlow framework.
• auto-modelling — A light package for automatic model tuning and stacking
• Auto-Taste-ML — A small example package
• auto-ts — Automatically Build Multiple Time Series models fast - now with Facebook Prophet!
• autoai-libs — A library of transformers to support portable representations of AutoAI pipelines
• autobmt — a modeling tool that automatically builds scorecards and tree models.
• autoboost — A thin wrapper for step-wise parameter optimization of boosting algorithms.
• AutoClassifierRegressor — Tools for getting analysis of all classifiers and regressors
• autodl-gpu — Automatic Deep Learning, towards fully automated multi-label classification for image, video, text, speech, tabular data.
• AutoEnsembler — This AutoEnsembler helps you to find the best Ensemble model for you
• AutoFeatSelect — Automated Feature Selection & Feature Importance Calculation Framework
• autoforecast — AutoML time series forecasting
• autogluon.tabular — Fast and Accurate ML in 3 Lines of Code
• autogluon-tonyhu-test.tabular — AutoML for Image, Text, and Tabular Data
• autoimpute — Imputation Methods in Python
• autom8 — Python AutoML library
• automl-alex — State-of-the art Automated Machine Learning python library for Tabular Data
• automl-tools — automl_tools
• AutoMLApp — An automated machine learning application designed for efficient model training, evaluation, and hyperparameter tuning.
• automlkiller — Auto machine learning, deep learning library in Python.
• automs — Automatic Model Selection Using Cluster Indices
• autoneuro-pypi — Template python package
• autonon — Organon Automated ML Platform
• autopilotml — A package for automating machine learning tasks
• autorad — Radiomics-related modules for extraction and experimenting
• autotonne — Auto machine learning, deep learning library in Python.
• autotrain-advanced — no summary
• autotreemodel — auto build a tree model
• AutoTS — Automated Time Series Forecasting
• autovf — autovf: tuning xgboost with optuna
• autoviml — Automatically Build Variant Interpretable ML models fast - now with CatBoost!
• autoviz — Automatically Visualize any dataset, any size with a single line of code
• autoxgb — autoxgb: tuning xgboost with optuna
• autoxgb-aucpr-bc — xgbauto: tuning xgboost with optuna, autoxgb with aucpr for binary classification
• autoxgbAUC — xgbauto: tuning xgboost with optuna, autoxgb with aucpr for binary classification
• ayx-learn — ['Ayx-learn alpha release.']
• azureml-train-automl — Used for automatically finding the best machine learning model and its parameters.
• BAMT — data modeling and analysis tool based on Bayesian networks
• bartbroere-eland — [Development fork!] Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch
• base2lines — a python package to benchmarks algorithms against various datasets
• baseline-optimal — no summary
• bayeso — Simple, but essential Bayesian optimization package
• bayte — Bayesian target encoding with scikit-learn and scipy
• bciavm — bciAVM is a machine learning pipeline used to predict property prices.
• bcml4pheno — Library for conducting, evaluating, and visualizing binary classification machine learning models for physics phenomenology.
• beexai — BEExAI: Benchmark to Evaluate Explainable AI
• benchscofi — Package which contains implementations of published collaborative filtering-based algorithms for drug repurposing.
• benderml — A Python package that makes ML processes easier, faster and less error prone
• best-optimal-algo — no summary
• bezzanlabs.treemachine — An AutoML companion to fit tree models easily
• bfscan — bfscan is designed to detect foodborne pathogens using bloom filter and machine learning
• bigquery-ml-utils — BigQuery ML Utils
• birdspotter — A package to measure the influence and botness of twitter users, from twitter dumps