Pylearn2 VS xgboost

Compare Pylearn2 vs xgboost and see what are their differences.

Pylearn2

Warning: This project does not have any current developer. See bellow. (by lisa-lab)

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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Pylearn2 xgboost
1 1
2,717 22,091
0.1% 0.9%
1.1 9.6
5 months ago 6 days ago
Python C++
BSD 3-clause "New" or "Revised" License 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.

Pylearn2

Posts with mentions or reviews of Pylearn2. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-08.
  • iNeural : Update (8.12.21)
    3 projects | dev.to | 8 Dec 2021
    It is developed by taking inspiration from libraries such as iNeural, FANN, pylearn2, EBLearn, Torch7. Written mostly in C++, iNeural also leverages the power of Python. The biggest reason for its development is that it needs very few dependencies. For this reason, it is expected to be suitable for working in systems with limited system requirements.

xgboost

Posts with mentions or reviews of xgboost. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Pylearn2 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

Keras - Deep Learning for humans

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.

mlpack - mlpack: a scalable C++ machine learning library --

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

MLflow - Open source platform for the machine learning lifecycle

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

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.

Surprise - A Python scikit for building and analyzing recommender systems

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)