Popularity

9.7

Declining

Activity

9.8

Growing

Stars 26,692

Watchers 905

Forks 8,751

Last Commit 2 days ago

Code Quality Rank: L1

Programming language: C++

License: Apache License 2.0

Tags: Machine Learning

Latest version: v1.3.0

xgboost alternatives and similar packages

Based on the "Machine Learning" category.
Alternatively, view xgboost alternatives based on common mentions on social networks and blogs.

scikit-learn

10.0 9.9 L3 xgboost VS scikit-learn

scikit-learn: machine learning in Python
tensorflow

10.0 10.0 L1 xgboost VS tensorflow

An Open Source Machine Learning Framework for Everyone

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Keras

9.9 9.9 L2 xgboost VS Keras

Deep Learning for humans
gym

9.8 0.0 xgboost VS gym

A toolkit for developing and comparing reinforcement learning algorithms.
MindsDB

9.7 9.9 xgboost VS MindsDB

AI's query engine - Platform for building AI that can learn and answer questions over large scale federated data.
PaddlePaddle

9.6 10.0 L1 xgboost VS PaddlePaddle

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
MLflow

9.5 9.9 xgboost VS MLflow

Open source platform for the machine learning lifecycle
Prophet

9.5 7.4 xgboost VS Prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
CNTK

9.5 0.0 L1 xgboost VS CNTK

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
gensim

9.4 5.7 L3 xgboost VS gensim

Topic Modelling for Humans
dspy

9.4 9.9 xgboost VS dspy

DSPy: The framework for programming—not prompting—language models
TFLearn

9.1 0.0 L3 xgboost VS TFLearn

Deep learning library featuring a higher-level API for TensorFlow.
NuPIC

8.8 0.0 L3 xgboost VS NuPIC

DISCONTINUED. Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.
H2O

8.7 9.1 xgboost VS H2O

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Pyro.ai

8.6 7.5 xgboost VS Pyro.ai

Deep universal probabilistic programming with Python and PyTorch
Surprise

8.4 5.1 L4 xgboost VS Surprise

A Python scikit for building and analyzing recommender systems
srez

8.3 0.0 L5 xgboost VS srez

DISCONTINUED. Image super-resolution through deep learning
LightFM

7.9 0.0 L4 xgboost VS LightFM

A Python implementation of LightFM, a hybrid recommendation algorithm.
Pylearn2

7.7 0.0 L2 xgboost VS Pylearn2

Warning: This project does not have any current developer. See bellow.
skflow

7.6 1.3 L4 xgboost VS skflow

DISCONTINUED. Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning
PyBrain

7.5 0.0 L4 xgboost VS PyBrain

Another Python Machine Learning Library.
Sacred

7.5 5.4 xgboost VS Sacred

Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
Clairvoyant

7.1 0.0 L3 xgboost VS Clairvoyant

Software designed to identify and monitor social/historical cues for short term stock movement
Atomic Agents

6.7 9.7 xgboost VS Atomic Agents

Building AI agents, atomically
garak, LLM vulnerability scanner

6.3 9.8 xgboost VS garak, LLM vulnerability scanner

DISCONTINUED. the LLM vulnerability scanner [Moved to: https://github.com/NVIDIA/garak]
karateclub

6.2 6.7 xgboost VS karateclub

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Metrics

6.2 0.0 xgboost VS Metrics

Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave
python-recsys

6.1 0.0 L4 xgboost VS python-recsys

A python library for implementing a recommender system
awesome-embedding-models

6.0 0.0 xgboost VS awesome-embedding-models

A curated list of awesome embedding models tutorials, projects and communities.
pydeep

5.8 0.0 L3 xgboost VS pydeep

Deep learning in Python
Crab

5.6 0.0 L2 xgboost VS Crab

Crab is a ﬂexible, fast recommender engine for Python that integrates classic information ﬁltering recommendation algorithms in the world of scientiﬁc Python packages (numpy, scipy, matplotlib).
hebel

5.0 0.0 L2 xgboost VS hebel

GPU-Accelerated Deep Learning Library in Python
seqeval

4.7 2.6 xgboost VS seqeval

A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)
adaptive

4.6 4.9 xgboost VS adaptive

:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
Xorbits

4.6 8.1 xgboost VS Xorbits

Scalable Python DS & ML, in an API compatible & lightning fast way.
TrueSkill, the video game rating system

4.2 1.4 xgboost VS TrueSkill, the video game rating system

An implementation of the TrueSkill rating system for Python
pdpipe

3.9 2.2 xgboost VS pdpipe

Easy pipelines for pandas DataFrames.
SciKit-Learn Laboratory

3.8 7.1 xgboost VS SciKit-Learn Laboratory

SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.
rwa

3.8 0.0 L5 xgboost VS rwa

Machine Learning on Sequential Data Using a Recurrent Weighted Average
nptyping

3.6 0.0 xgboost VS nptyping

💡 Type hints for Numpy and Pandas
Robocorp Action Server

3.6 7.7 xgboost VS Robocorp Action Server

Create 🐍 Python AI Actions and 🤖 Automations, and deploy & operate them anywhere
Feature Forge

3.5 0.0 L4 xgboost VS Feature Forge

A set of tools for creating and testing machine learning features, with a scikit-learn compatible API
Data Flow Facilitator for Machine Learning (dffml)

3.3 9.3 xgboost VS Data Flow Facilitator for Machine Learning (dffml)

DISCONTINUED. The easiest way to use Machine Learning. Mix and match underlying ML libraries and data set sources. Generate new datasets or modify existing ones with ease.
brew

3.2 0.0 L4 xgboost VS brew

DISCONTINUED. Multiple Classifier Systems and Ensemble Learning Library in Python.
bodywork

3.1 0.0 xgboost VS bodywork

DISCONTINUED. ML pipeline orchestration and model deployments on Kubernetes.
redframes

2.8 1.4 xgboost VS redframes

General Purpose Data Manipulation Library
MLP Classifier

2.8 0.0 L4 xgboost VS MLP Classifier

A handwritten multilayer perceptron classifer using numpy.
openskill.py

2.7 7.1 xgboost VS openskill.py

Multiplayer Rating System. No Friction.
OptaPy

2.7 5.5 xgboost VS OptaPy

OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.
vowpal_porpoise

2.5 0.0 L3 xgboost VS vowpal_porpoise

lightweight python wrapper for vowpal wabbit

* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.

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README

eXtreme Gradient Boosting

[ GitHub license ](./LICENSE)

Community | Documentation | [Resources](demo/README.md) | [Contributors](CONTRIBUTORS.md) | [Release Notes](NEWS.md)

XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. The same code runs on major distributed environment (Kubernetes, Hadoop, SGE, MPI, Dask) and can solve problems beyond billions of examples.

License

Contribute to XGBoost

XGBoost has been developed and used by a group of active community members. Your help is very valuable to make the package better for everyone. Checkout the Community Page.

Reference

Tianqi Chen and Carlos Guestrin. XGBoost: A Scalable Tree Boosting System. In 22nd SIGKDD Conference on Knowledge Discovery and Data Mining, 2016
XGBoost originates from research project at University of Washington.