CXXGraph VS LightGBM

Compare CXXGraph vs LightGBM and see what are their differences.

LightGBM

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. (by Microsoft)
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CXXGraph LightGBM
84 11
381 15,962
- 0.9%
8.5 9.2
9 days ago 3 days ago
C++ C++
GNU Affero General Public License v3.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

CXXGraph

Posts with mentions or reviews of CXXGraph. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-09.

LightGBM

Posts with mentions or reviews of LightGBM. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-29.
  • SIRUS.jl: Interpretable Machine Learning via Rule Extraction
    2 projects | /r/Julia | 29 Jun 2023
    SIRUS.jl is a pure Julia implementation of the SIRUS algorithm by Bénard et al. (2021). The algorithm is a rule-based machine learning model meaning that it is fully interpretable. The algorithm does this by firstly fitting a random forests and then converting this forest to rules. Furthermore, the algorithm is stable and achieves a predictive performance that is comparable to LightGBM, a state-of-the-art gradient boosting model created by Microsoft. Interpretability, stability, and predictive performance are described in more detail below.
  • What's New with AWS: Amazon SageMaker built-in algorithms now provides four new Tabular Data Modeling Algorithms
    3 projects | dev.to | 28 Jun 2022
    LightGBM is a popular and high-performance open-source implementation of the Gradient Boosting Decision Tree (GBDT). To learn how to use this algorithm, please see example notebooks for Classification and Regression.
  • Search YouTube from the terminal written in python
    2 projects | /r/Python | 28 Feb 2022
    Microsoft lightGBM. https://github.com/microsoft/LightGBM
  • LightGBM VS CXXGraph - a user suggested alternative
    2 projects | 28 Feb 2022
  • Writing the fastest GBDT libary in Rust
    6 projects | dev.to | 11 Jan 2022
    Here are our benchmarks on training time comparing Tangram's Gradient Boosted Decision Tree Library to LightGBM, XGBoost, CatBoost, and sklearn.
  • Workstation Management With Nix Flakes: Build a Cmake C++ Package
    2 projects | dev.to | 31 Oct 2021
    { inputs = { nixpkgs = { url = "github:nixos/nixpkgs/nixos-unstable"; }; flake-utils = { url = "github:numtide/flake-utils"; }; }; outputs = { nixpkgs, flake-utils, ... }: flake-utils.lib.eachDefaultSystem (system: let pkgs = import nixpkgs { inherit system; }; lightgbm-cli = (with pkgs; stdenv.mkDerivation { pname = "lightgbm-cli"; version = "3.3.1"; src = fetchgit { url = "https://github.com/microsoft/LightGBM"; rev = "v3.3.1"; sha256 = "pBrsey0RpxxvlwSKrOJEBQp7Hd9Yzr5w5OdUuyFpgF8="; fetchSubmodules = true; }; nativeBuildInputs = [ clang cmake ]; buildPhase = "make -j $NIX_BUILD_CORES"; installPhase = '' mkdir -p $out/bin mv $TMP/LightGBM/lightgbm $out/bin ''; } ); in rec { defaultApp = flake-utils.lib.mkApp { drv = defaultPackage; }; defaultPackage = lightgbm-cli; devShell = pkgs.mkShell { buildInputs = with pkgs; [ lightgbm-cli ]; }; } ); }
  • Is it possible to clean memory after using a package that has a memory leak in my python script?
    2 projects | /r/Python | 29 Apr 2021
    I'm working on the AutoML python package (Github repo). In my package, I'm using many different algorithms. One of the algorithms is LightGBM. The algorithm after the training doesn't release the memory, even if del is called and gc.collect() after. I created the issue on LightGBM GitHub -> link. Because of this leak, memory consumption is growing very fast during algorithm training.

What are some alternatives?

When comparing CXXGraph and LightGBM you can also consider the following projects:

tensorflow - An Open Source Machine Learning Framework for Everyone

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.

GPBoost - Combining tree-boosting with Gaussian process and mixed effects models

amazon-sagemaker-examples - Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

yggdrasil-decision-forests - A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.

mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

decision-tree-classifier - Decision Tree Classifier and Boosted Random Forest

pyvirtualcam - 🎥 Send frames to a virtual camera from Python

sirix - SirixDB is an an embeddable, bitemporal, append-only database system and event store, storing immutable lightweight snapshots. It keeps the full history of each resource. Every commit stores a space-efficient snapshot through structural sharing. It is log-structured and never overwrites data. SirixDB uses a novel page-level versioning approach.

rstan - RStan, the R interface to Stan