CNTK VS xgboost

Compare CNTK vs xgboost and see what are their differences.

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 (by dmlc)
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CNTK xgboost
1 10
17,435 25,438
0.0% 0.7%
0.0 9.7
about 1 year ago 7 days ago
C++ C++
GNU General Public License v3.0 or later Apache License 2.0
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.

CNTK

Posts with mentions or reviews of CNTK. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-20.

xgboost

Posts with mentions or reviews of xgboost. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-09.
  • PSA: You don't need fancy stuff to do good work.
    10 projects | /r/datascience | 9 May 2023
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive documentation and community support, making it easy to learn and apply new techniques without needing specialized training or expensive software licenses.
  • xgboost VS CXXGraph - a user suggested alternative
    2 projects | 28 Feb 2022

What are some alternatives?

When comparing CNTK and xgboost you can also consider the following projects:

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

MLP Classifier - A handwritten multilayer perceptron classifer using numpy.

tensorflow - An Open Source Machine Learning Framework for Everyone

Theano - Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as PyTensor: www.github.com/pymc-devs/pytensor

Keras - Deep Learning for humans

mlpack - mlpack: a fast, header-only C++ machine learning library

catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

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

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

scikit-learn - scikit-learn: machine learning in Python

Caffe - Caffe: a fast open framework for deep learning.