20 projects found that use the apache 2.0 license.
Showing Items 1-20 of 33 on page 1 of 2: 1 2 Next

Logo AMIDST Toolbox 0.6.0

by ana - October 14, 2016, 19:35:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4269 views, 651 downloads, 4 subscriptions

About: A Java Toolbox for Scalable Probabilistic Machine Learning.

  • Added sparklink module implementing the integration with Apache Spark. More information here.
  • Fluent pattern in latent-variable-models
  • Predefined model implementing the concept drift detection

Detailed information can be found in the toolbox's web page

Logo revrand 0.7.0

by dsteinberg - October 14, 2016, 08:31:02 CET [ Project Homepage BibTeX Download ] 6508 views, 1222 downloads, 3 subscriptions

About: A library of scalable Bayesian generalised linear models with fancy features

  • Ability to set the random state in all random basis functions, optimisers and the generalised linear model
  • Numerous numerical bug fixes
  • small performance optimisations

Logo KeLP 2.1.0

by kelpadmin - August 11, 2016, 10:40:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11303 views, 2558 downloads, 3 subscriptions

About: Kernel-based Learning Platform (KeLP) is Java framework that supports the implementation of kernel-based learning algorithms, as well as an agile definition of kernel functions over generic data representation, e.g. vectorial data or discrete structures. The framework has been designed to decouple kernel functions and learning algorithms, through the definition of specific interfaces. Once a new kernel function has been implemented, it can be automatically adopted in all the available kernel-machine algorithms. KeLP includes different Online and Batch Learning algorithms for Classification, Regression and Clustering, as well as several Kernel functions, ranging from vector-based to structural kernels. It allows to build complex kernel machine based systems, leveraging on JSON/XML interfaces to instantiate prediction models without writing a single line of code.


In addition to minor bug fixes, this release includes:

  • a flexible system to manipulate example-pairs
  • new manipulators for performing tree pruning
  • new examples for the usage of kelp

Check out this new version from our repositories. API Javadoc is already available. Your suggestions will be very precious for us, so download and try KeLP 2.1.0!

Logo Toupee 0.1

by nitbix - March 7, 2016, 20:29:59 CET [ Project Homepage BibTeX Download ] 984 views, 244 downloads, 3 subscriptions

About: A Python based library for running experiments with Deep Learning and Ensembles on GPUs.


Initial Announcement on mloss.org.

Logo PROFET 1.0.0

by Hamda - November 26, 2015, 13:20:28 CET [ Project Homepage BibTeX Download ] 1288 views, 358 downloads, 2 subscriptions

About: Software for Automatic Construction and Inference of DBNs Based on Mathematical Models


Initial Announcement on mloss.org.

About: Efficient and Flexible Distributed/Mobile Deep Learning Framework, for python, R, Julia and more


This version comes with Distributed and Mobile Examples

Logo Apache Mahout 0.11.1

by gsingers - November 9, 2015, 16:12:06 CET [ Project Homepage BibTeX Download ] 22642 views, 5849 downloads, 3 subscriptions

About: Apache Mahout is an Apache Software Foundation project with the goal of creating both a community of users and a scalable, Java-based framework consisting of many machine learning algorithm [...]


Apache Mahout introduces a new math environment we call Samsara, for its theme of universal renewal. It reflects a fundamental rethinking of how scalable machine learning algorithms are built and customized. Mahout-Samsara is here to help people create their own math while providing some off-the-shelf algorithm implementations. At its core are general linear algebra and statistical operations along with the data structures to support them. You can use is as a library or customize it in Scala with Mahout-specific extensions that look something like R. Mahout-Samsara comes with an interactive shell that runs distributed operations on a Spark cluster. This make prototyping or task submission much easier and allows users to customize algorithms with a whole new degree of freedom. Mahout Algorithms include many new implementations built for speed on Mahout-Samsara. They run on Spark 1.3+ and some on H2O, which means as much as a 10x speed increase. You’ll find robust matrix decomposition algorithms as well as a Naive Bayes classifier and collaborative filtering. The new spark-itemsimilarity enables the next generation of cooccurrence recommenders that can use entire user click streams and context in making recommendations.

Logo XGBoost v0.4.0

by crowwork - May 12, 2015, 08:57:16 CET [ Project Homepage BibTeX Download ] 14991 views, 2674 downloads, 3 subscriptions

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily. The newest version of xgboost now supports distributed learning on various platforms such as hadoop, mpi and scales to even larger problems

  • Distributed version of xgboost that runs on YARN, scales to billions of examples

  • Direct save/load data and model from/to S3 and HDFS

  • Feature importance visualization in R module, by Michael Benesty

  • Predict leaf index

  • Poisson regression for counts data

  • Early stopping option in training

  • Native save load support in R and python

  • xgboost models now can be saved using save/load in R

  • xgboost python model is now pickable

  • sklearn wrapper is supported in python module

  • Experimental External memory version

Logo streamDM 0.0.1

by abifet - April 28, 2015, 12:34:00 CET [ Project Homepage BibTeX Download ] 2001 views, 732 downloads, 1 subscription

About: streamDM is a new open source data mining and machine learning library, designed on top of Spark Streaming, an extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of data streams.


Initial Announcement on mloss.org.

Logo Hivemall 0.3

by myui - March 13, 2015, 17:08:22 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10438 views, 1829 downloads, 3 subscriptions

About: Hivemall is a scalable machine learning library running on Hive/Hadoop.

  • Supported Matrix Factorization
  • Added a support for TF-IDF computation
  • Supported AdaGrad/AdaDelta
  • Supported AdaGradRDA classification
  • Added normalization scheme

Logo Rabit 0.1.0

by crowwork - January 21, 2015, 18:48:46 CET [ Project Homepage BibTeX Download ] 1793 views, 592 downloads, 1 subscription

About: rabit (Reliable Allreduce and Broadcast Interface) is a light weight library that provides a fault tolerant interface of Allreduce and Broadcast for portable , scalable and reliable distributed machine learning programs. Rabit programs can run on various platforms such as Hadoop, MPI and no installation is needed. Rabit now support kmeans clustering, and distributed xgboost: an extremely efficient disrtibuted boosted tree(GBDT) toolkit.


Initial Announcement on mloss.org.

Logo ExtRESCAL 0.7.2

by nzhiltsov - January 20, 2015, 00:35:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8172 views, 1535 downloads, 2 subscriptions

About: Scalable tensor factorization

  • Improve (speed up) initialization of A by summation

Logo Semi Stochastic Gradient Descent 1.0

by konkey - July 9, 2014, 04:28:47 CET [ BibTeX BibTeX for corresponding Paper Download ] 3184 views, 859 downloads, 1 subscription

About: Efficient implementation of Semi-Stochastic Gradient Descent algorithm (S2GD) for training logistic regression (L2-regularized).


Initial Announcement on mloss.org.

Logo Encog Machine Learning Framework 3.2

by jeffheaton - July 5, 2014, 23:47:06 CET [ Project Homepage BibTeX Download ] 6717 views, 2309 downloads, 1 subscription

About: Encog is a Machine Learning framework for Java, C#, Javascript and C/C++ that supports SVM's, Genetic Programming, Bayesian Networks, Hidden Markov Models and other algorithms.


Changes for Encog 3.2:

Issue #53: Fix Out Of Range Bug In BasicMLSequenceSet. Issue #52: Unhandled exception in Encog.Util.File.ResourceLoader.CreateStream (ResourceLoader.cs) Issue #50: Concurrency bugs in PruneIncremental Issue #48: Unit Tests Failing - TestHessian Issue #46: Couple of small fixes - Temporal DataSet and SCG training Issue #45: Fixed EndMinutesStrategy to correctly evaluate ShouldStop after the specified number of minutes have elapsed. Issue #44: Encog.ML.Data.Basic.BasicMLDataPairCentroid.Add() & .Remove() Issue #43: Unit Tests Failing - Matrix not full rank Issue #42: Nuget - NuSpec Issue #36: Load Examples easier

About: RLLib is a lightweight C++ template library that implements incremental, standard, and gradient temporal-difference learning algorithms in Reinforcement Learning. It is an optimized library for robotic applications and embedded devices that operates under fast duty cycles (e.g., < 30 ms). RLLib has been tested and evaluated on RoboCup 3D soccer simulation agents, physical NAO V4 humanoid robots, and Tiva C series launchpad microcontrollers to predict, control, learn behaviors, and represent learnable knowledge. The implementation of the RLLib library is inspired by the RLPark API, which is a library of temporal-difference learning algorithms written in Java.


Current release version is v2.0.

Logo MShadow 1.0

by antinucleon - April 10, 2014, 02:57:54 CET [ Project Homepage BibTeX Download ] 2530 views, 731 downloads, 1 subscription

About: Lightweight CPU/GPU Matrix/Tensor Template Library in C++/CUDA. Support element-wise expression expand in high performance. Code once, run smoothly on both GPU and CPU


Initial Announcement on mloss.org.

Logo CXXNET 0.1

by antinucleon - April 10, 2014, 02:47:08 CET [ Project Homepage BibTeX Download ] 3250 views, 768 downloads, 1 subscription

About: CXXNET (spelled as: C plus plus net) is a neural network toolkit build on mshadow(https://github.com/tqchen/mshadow). It is yet another implementation of (convolutional) neural network. It is in C++, with about 1000 lines of network layer implementations, easily configuration via config file, and can get the state of art performance.


Initial Announcement on mloss.org.

Logo SAMOA 0.0.1

by gdfm - April 2, 2014, 17:09:08 CET [ Project Homepage BibTeX Download ] 2223 views, 623 downloads, 2 subscriptions

About: SAMOA is a platform for mining big data streams. It is a distributed streaming machine learning (ML) framework that contains a programing abstraction for distributed streaming ML algorithms.


Initial Announcement on mloss.org.

Logo HierLearning 1.0

by neville - March 2, 2014, 04:24:37 CET [ BibTeX BibTeX for corresponding Paper Download ] 2599 views, 724 downloads, 1 subscription

About: HierLearning is a C++11 implementation of a general-purpose, multi-agent, hierarchical reinforcement learning system for sequential decision problems.


Initial Announcement on mloss.org.

Logo A Parallel LDA Learning Toolbox 1.0

by yanjianfeng - January 24, 2014, 11:48:07 CET [ BibTeX Download ] 3042 views, 1136 downloads, 1 subscription

About: We introduces PLL, a parallel LDA learning toolbox for big topic modeling.


Fix some compiling errors.

Showing Items 1-20 of 33 on page 1 of 2: 1 2 Next