Reverse Dependencies of xgboost
The following projects have a declared dependency on xgboost:
- bixai — Package that makes it a bit easier to understand some complex models and helps you visualize them
- black-it — black-it: Black-box abm calibration kit
- blackbeard2109 — This library is designed for people who need to optimize time in an agile way with an ease of understanding and could
- blackfox-extras — BlackFox Extras
- blobcity — Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.
- blossomai — blossomAI automates data exploration and visualization
- bluecast — A lightweight and fast automl framework
- bofire — no summary
- bokbokbok — Custom Losses and Metrics for XGBoost, LightGBM, CatBoost
- bonsai-tree — Bayesian Optimization + Gradient Boosted Trees
- boost-loss — Utilities for easy use of custom losses in CatBoost, LightGBM, XGBoost
- boostaroota — A Fast XGBoost Feature Selection Algorithm
- booster-wrappers — Booster Wrappers
- bqml-xgboost-predictor — BQML XGBoost Predictor
- brain-pred-toolbox — The Brain Predictability toolbox (BPt) is a Python based machine learning library designed to work with a range of neuroimaging data. Warning: Not actively maintained as of 11/30/22.
- brainome — Brainome Table Compiler
- brainome-linux-python3.7 — Brainome Table Compiler
- brainome-linux-python3.8 — Brainome Table Compiler
- brainome-linux-python3.9 — Brainome Table Compiler
- brainome-mac-python3.7 — Brainome Table Compiler
- brainome-mac-python3.8 — Brainome Table Compiler
- brainome-mac-python3.9 — Brainome Table Compiler
- BrainStrokeClassifier — Brain Stroke Classfier using Machine Learning!
- brebsML — Toutes les librairies que nous utiliseront pour ce comité
- broadsteel-datascience — BroadSteel_DataScience
- bs-ds — A collection of tools from bootcamp.
- bugbug — ML tools for Mozilla projects
- building-controller-forecast — Building controller forecasting lib
- bytetrade-recommend-model-sdk — no summary
- c3pred — Prediction of cargo transport potential of short peptides.
- caliber — Model-agnostic calibration and performance enhancement.
- Cannai — data visualization for machine learning
- carla-recourse — A library for counterfactual recourse
- carom-sblab — An awesome package that does something
- CATCHM — A novel network-based credit card fraud detection approach using noderepresentation learning
- catenets — Conditional Average Treatment Effect Estimation Using Neural Networks
- causallift — CausalLift: Python package for Uplift Modeling for A/B testing and observational data.
- causalml — Python Package for Uplift Modeling and Causal Inference with Machine Learning Algorithms
- CCIT — Model Powered CI Test
- cellcanvas — A tool for painting in cellular architecture
- cellgrid — Cell classification by learning known phenotypes
- ceruleo — Remaining useful life estimation utilities
- cfbfastR-py — Retrieve American football data in Python
- cgem — CGEM: Collaborative Generalized Effects Modeling
- chady — A package for ML libraries
- changtianml — no summary
- chickenstats — A Python package for scraping & analyzing sports statistics
- ciclops — Pipeline for building clinical outcome prediction models on training dataset and transfer learning on validation datasets.
- CIMLA — Counterfactual Inference by Machine Learning and Attribution Models
- cinnamon — A monitoring tool for machine learning systems that focus on data drift
- classification-algorithm — All classifier algorithm at one place
- classification-model — Classification model for animal activity recognition based on XGBoost
- clep — A Hybrid Data and Knowledge Driven Framework for Generating Patient Representations
- climaticai — climaticai is a library that builds, optimizes, and evaluates machine learning pipelines
- clin-msi — The workflow package for MSI detection in Python
- clinica — Software platform for clinical neuroimaging studies
- clust-learn — A Python package for explainable cluster analysis
- co2mpas — The Type-Approving vehicle simulator predicting NEDC CO2 emissions from WLTP
- co2mpas-driver — A lightweight microsimulation free-flow acceleration model(MFC) or co2mpas_driver is a model that is able to capture the vehicle acceleration dynamics accurately and consistently
- coiled-runtime — Simple and fast way to get started with Dask
- colearn — The Standalone Fetch AI Collective Learning Framework
- competitions — Hugging Face Competitions
- concrete-ml — Concrete ML is an open-source set of tools which aims to simplify the use of fully homomorphic encryption (FHE) for data scientists.
- concrete-ml-extensions-hb — Convert trained traditional machine learning models into tensor computations
- conformal-tights — A scikit-learn meta-estimator for computing tight conformal predictions
- conveyer — Automated machine learning library
- core-of-theaisphere — Package sitting at the core of theAIsphere
- core-pro — A utility package for data science
- coreml — Generic Framework for ML projects
- corsid — Core Sequence Identifier
- crosspredict — package for easy crossvalidation
- crossval-ensemble — A scikit-learn wrapper for CrossValidation Ensembles
- customer-churn-classification-model — classification model package from Train In Data.
- cutoml — A lightweight automl framework
- cv19index — COVID-19 Vulnerability Index
- cyc-pep-perm — Python package to predict membrane permeability of cyclic peptides.
- cytopy — Data centric algorithm agnostic cytometry analysis framework
- d3m-common-primitives — D3M common primitives
- dankag — utilities for kaggle competitions
- darts — A python library for easy manipulation and forecasting of time series.
- darwin-mendel — Genetic Algorithm: Optimize the output of machine learning models
- dask-ml — A library for distributed and parallel machine learning
- dask-xgboost — Interactions between Dask and XGBoost
- data-dashboard — Dashboard to explore the data and to create baseline Machine Learning model.
- data-iq — Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data
- data-science-pipeline-automation — Python library to help you to automate the data science pipeline
- data-science-toolkit — Data Science Toolkit (DST) is a Python library that helps implement data science related project with ease.
- datadm — DataDM is your private data assistant. Slide into your data's DMs
- datarobot-drum — Custom Model Runner
- datarobotx — DataRobotX is a collection of DataRobot extensions
- datascienv — Data Science package for setup data science environment in single line
- datto — Data Tools (Dat To)
- datupapi — Utility library to support Datup AI MLOps processes
- dbest — Model-based Approximate Query Processing (AQP) engine.
- dbgym — DBGym: platform for ML research and application on databases
- dbt-layer — The Layer adapter plugin for dbt
- dbt-layer-bigquery — The Layer / BigQuery adapter plugin for dbt
- decaf-synthetic-data — DEbiasing CAusal Fairness
- deep-kolibri — Deep Learning and more NLP toolkit
- deepBreaks — deepBreaks: a machine learning tool for identifying and prioritizing genotype-phenotype associations