Projects supporting the numpy data format.

Logo rupture, change point detection in Python 1.0

by truongx - January 3, 2018, 09:51:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1271 views, 331 downloads, 2 subscriptions

About: ruptures is a Python library for off-line change point detection. This package provides methods for the analysis and segmentation of non-stationary signals. Implemented algorithms include exact and approximate detection for various parametric and non-parametric models. ruptures focuses on ease of use by providing a well-documented and consistent interface. In addition, thanks to its modular structure, different algorithms and models can be connected and extended within this package.


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Logo Accord.NET Framework 3.8.0

by cesarsouza - October 23, 2017, 20:50:27 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 44506 views, 7486 downloads, 2 subscriptions

About: The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and an extensive online documentation helps fill in the details.


For a complete list of changes, please see the full release notes at the release details page at:

Logo bufferkdtree 1.3

by fgieseke - October 20, 2017, 11:39:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 933 views, 193 downloads, 2 subscriptions

About: The bufferkdtree package is a Python library that aims at accelerating nearest neighbor computations using both k-d trees and modern many-core devices such as graphics processing units (GPUs).


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Logo scikit multilearn 0.0.5

by niedakh - February 25, 2017, 03:51:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4987 views, 1084 downloads, 3 subscriptions

About: A native Python, scikit-compatible, implementation of a variety of multi-label classification algorithms.

  • a general matrix-based label space clusterer has been added which can cluster the output space using any scikit-learn compatible clusterer (incl. k-means)
  • support for more single-class and multi-class classifiers you can now use problem transformation approaches with your favourite neural networks/deep learning libraries: theano, tensorflow, keras, scikit-neuralnetworks
  • support for label powerset based stratified kfold added
  • graph-tool clusterer supports weighted graphs again and includes stochastic blockmodel calibration
  • bugs were fixed in: classifier chains and hierarchical neuro fuzzy clasifiers

Logo revrand 1.0.0

by dsteinberg - January 29, 2017, 04:33:54 CET [ Project Homepage BibTeX Download ] 18592 views, 3932 downloads, 3 subscriptions

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

  • 1.0 release!
  • Now there is a random search phase before optimization of all hyperparameters in the regression algorithms. This improves the performance of revrand since local optima are more easily avoided with this improved initialisation
  • Regression regularizers (weight variances) associated with each basis object, this approximates GP kernel addition more closely
  • Random state can be set for all random objects
  • Numerous small improvements to make revrand production ready
  • Final report
  • Documentation improvements

Logo RLScore 0.7

by aatapa - September 20, 2016, 09:51:25 CET [ Project Homepage BibTeX Download ] 2334 views, 600 downloads, 3 subscriptions

About: RLScore - regularized least-squares machine learning algorithms package


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Logo libcluster 2.3

by dsteinberg - February 27, 2016, 00:36:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8169 views, 1613 downloads, 3 subscriptions

About: An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.


New maximum cluster argument for all algorithms. Also no more matlab interface since it seemed no one was using it, and I cannot support it any longer.

Logo XGBoost v0.4.0

by crowwork - May 12, 2015, 08:57:16 CET [ Project Homepage BibTeX Download ] 20972 views, 3693 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 Machine Learning Support System MALSS 0.5.0

by canard0328 - February 20, 2015, 15:56:02 CET [ Project Homepage BibTeX Download ] 2776 views, 789 downloads, 1 subscription

About: MALSS is a python module to facilitate machine learning tasks.


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Logo pyGPs 1.3.2

by mn - January 17, 2015, 13:08:43 CET [ Project Homepage BibTeX Download ] 12520 views, 2782 downloads, 4 subscriptions

About: pyGPs is a Python package for Gaussian process (GP) regression and classification for machine learning.


Changelog pyGPs v1.3.2

December 15th 2014

  • pyGPs added to pip
  • mathematical definitions of kernel functions available in documentation
  • more error message added

Logo linearizedGP 1.0

by dsteinberg - November 28, 2014, 07:02:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3738 views, 766 downloads, 1 subscription

About: Gaussian processes with general nonlinear likelihoods using the unscented transform or Taylor series linearisation.


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Logo pySPACE 1.2

by krell84 - October 29, 2014, 15:36:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9075 views, 1688 downloads, 1 subscription

About: pySPACE is the abbreviation for "Signal Processing and Classification Environment in Python using YAML and supporting parallelization". It is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface.


improved testing, improved documentation, windows compatibility, more algorithms

Logo Crino 1.0.0

by jlerouge - July 16, 2014, 17:54:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4038 views, 922 downloads, 2 subscriptions

About: Crino: a neural-network library based on Theano


1.0.0 (7 july 2014) : - Initial release of crino - Implements a torch-like library to build artificial neural networks (ANN) - Provides standard implementations for : * auto-encoders * multi-layer perceptrons (MLP) * deep neural networks (DNN) * input output deep architecture (IODA) - Provides a batch-gradient backpropagation algorithm, with adaptative learning rate

Logo epac 0.10

by jinpengli - October 9, 2013, 14:00:15 CET [ Project Homepage BibTeX Download ] 4951 views, 1051 downloads, 1 subscription

About: Embarrassingly Parallel Array Computing: EPAC is a machine learning workflow builder.


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Logo OpenANN 1.1.0

by afabisch - September 26, 2013, 23:52:03 CET [ Project Homepage BibTeX Download ] 7807 views, 1539 downloads, 2 subscriptions

About: A library for artificial neural networks.


Added algorithms:

  • L-BFGS optimizer
  • k-means
  • sparse auto-encoder
  • preprocessing: normalization, PCA, ZCA whitening

Logo OptWok 0.3.1

by ong - May 2, 2013, 10:46:11 CET [ Project Homepage BibTeX Download ] 14866 views, 2924 downloads, 1 subscription

About: A collection of python code to perform research in optimization. The aim is to provide reusable components that can be quickly applied to machine learning problems. Used in: - Ellipsoidal multiple instance learning - difference of convex functions algorithms for sparse classfication - Contextual bandits upper confidence bound algorithm (using GP) - learning output kernels, that is kernels between the labels of a classifier.

  • minor bugfix

Logo treelearn 1

by iskander - September 21, 2011, 16:12:27 CET [ Project Homepage BibTeX Download ] 4825 views, 1243 downloads, 1 subscription

About: A python implementation of Breiman's Random Forests.


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Logo reserbot alpha 1

by neuromancer - January 31, 2011, 14:27:18 CET [ Project Homepage BibTeX Download ] 8835 views, 2012 downloads, 1 subscription

About: A chatterbot that learns natural languages learning from imitation.


Alpha 1 - Codename: Wendell Borton ("Bllluuhhhhh...!!")

Short term memory greatly improved.