20 projects found that use the bsd license.
Showing Items 1-20 of 70 on page 1 of 4: 1 2 3 4 Next

Logo Optunity 0.2.0

by claesenm - July 24, 2014, 10:07:54 CET [ Project Homepage BibTeX Download ] 184 views, 36 downloads, 1 subscription

About: Optunity is a library containing various optimizers for hyperparameter tuning. Hyperparameter tuning is a recurrent problem in many machine learning tasks, both supervised and unsupervised.This package provides several distinct approaches to solve such problems including some helpful facilities such as cross-validation and a plethora of score functions.

Changes:

Initial Announcement on mloss.org.


Logo pyGPs 1.2

by mn - July 17, 2014, 10:28:55 CET [ Project Homepage BibTeX Download ] 1509 views, 372 downloads, 2 subscriptions

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

Changes:

Changelog pyGPs v1.2

June 30th 2014

structural updates:

  • input target now can either be in 2-d array with size (n,1) or in 1-d array with size (n,)
  • setup.py updated
  • "import pyGPs" instead of "from pyGPs.Core import gp"
  • rename ".train()" to ".optimize()"
  • rename "Graph-stuff" to "graphExtension"
  • rename kernelOnGraph to "nodeKernels" and graphKernel to "graphKernels"
  • redundancy removed for model.setData(x,y)
  • rewrite "mean.proceed()" to "getMean()" and "getDerMatrix()"
  • rewrite "cov.proceed()" to "getCovMatrix()" and "getDerMatrix()"
  • rename cov.LIN to cov.Linear (to be consistent with mean.Linear)
  • rename module "valid" to "validation"
  • add graph dataset Mutag in python file. (.npz and .mat)
  • add graphUtil.nomalizeKernel()
  • fix number of iteration problem in graphKernels "PropagationKernel"
  • add unit testing for covariance, mean functions

bug fixes:

  • derivatives for cov.LINard
  • derivative of the scalar for cov.covScale
  • demo_GPR_FITC.py missing pyGPs.mean

July 8th 2014

structural updates:

  • add hyperparameter(signal variance s2) for linear covariance
  • add unit testing for inference,likelihood functions as well as models
  • NOT show(print) "maximum number of sweep warning in inference EP" any more
  • documentation updated

bug fixes:

  • typos in lik.Laplace
  • derivative in lik.Laplace

July 14th 2014

documentation updates:

  • online docs updated
  • API file updated

structural updates:

  • made private for methods that users don't need to call

Logo PyStruct 0.2

by t3kcit - July 9, 2014, 09:29:23 CET [ Project Homepage BibTeX Download ] 1310 views, 389 downloads, 1 subscription

About: PyStruct is a framework for learning structured prediction in Python. It has a modular interface, similar to the well-known SVMstruct. Apart from learning algorithms it also contains model formulations for popular CRFs and interfaces to many inference algorithm implementation.

Changes:

Initial Announcement on mloss.org.


Logo FEAST 1.1.1

by apocock - June 30, 2014, 01:30:23 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13808 views, 3281 downloads, 1 subscription

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About: FEAST provides implementations of common mutual information based filter feature selection algorithms (mim, mifs, mrmr, cmim, icap, jmi, disr, fcbf, etc), and an implementation of RELIEF. Written for C/C++ & Matlab.

Changes:
  • Bug fixes to memory management.
  • Compatibility changes for PyFeast python wrapper (note the C library now returns feature indices starting from 0, the Matlab wrapper still returns indices starting from 1).
  • Added C version of MIM.
  • Updated internal version of MIToolbox.

Logo OpenOpt 0.54

by Dmitrey - June 15, 2014, 14:50:37 CET [ Project Homepage BibTeX Download ] 39667 views, 8335 downloads, 3 subscriptions

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About: Universal Python-written numerical optimization toolbox. Problems: NLP, LP, QP, NSP, MILP, LSP, LLSP, MMP, GLP, SLE, MOP etc; general logical constraints, categorical variables, automatic differentiation, stochastic programming, interval analysis, many other goodies

Changes:

http://openopt.org/Changelog


Logo Caffe 0.999

by sergeyk - May 20, 2014, 23:51:09 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2411 views, 383 downloads, 2 subscriptions

About: Caffe aims to provide computer vision scientists with a clean, modifiable implementation of state-of-the-art deep learning algorithms. We believe that Caffe is the fastest available GPU CNN implementation. Caffe also provides seamless switching between CPU and GPU, which allows one to train models with fast GPUs and then deploy them on non-GPU clusters. Even in CPU mode, computing predictions on an image takes only 20 ms (in batch mode).

Changes:

https://github.com/BVLC/caffe/releases/tag/v0.999


Logo JMLR Tapkee 1.0

by blackburn - April 10, 2014, 02:45:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5137 views, 1403 downloads, 1 subscription

About: Tapkee is an efficient and flexible C++ template library for dimensionality reduction.

Changes:

Initial Announcement on mloss.org.


Logo DRVQ 1.0.1-beta

by iavr - January 18, 2014, 17:26:34 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 816 views, 184 downloads, 1 subscription

About: DRVQ is a C++ library implementation of dimensionality-recursive vector quantization, a fast vector quantization method in high-dimensional Euclidean spaces under arbitrary data distributions. It is an approximation of k-means that is practically constant in data size and applies to arbitrarily high dimensions but can only scale to a few thousands of centroids. As a by-product of training, a tree structure performs either exact or approximate quantization on trained centroids, the latter being not very precise but extremely fast.

Changes:

Initial Announcement on mloss.org.


Logo JMLR Darwin 1.7

by sgould - January 10, 2014, 01:33:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 25371 views, 5387 downloads, 2 subscriptions

About: A platform-independent C++ framework for machine learning, graphical models, and computer vision research and development.

Changes:

Version 1.7:

  • Log file now shows the command line
  • Utility application added for viewing multi-class segmentation legend
  • Added LBP filter response features to multi-class segmentation model
  • Added drwnColourHistogram class
  • Added k-means segmentation method for creating superpixels
  • Application visualizeSuperpixels and mex routines for loading and saving superpixels
  • Improved mex parsing of Matlab objects to support more matrix types
  • Bug fix in drwnOptimizer (thanks to Subarna Tripathi)
  • Updated copyright notice to 2007-2014
  • Other bug fixes and performance improvements

Version 1.6.1:

  • Maximum size of drwnShowDebuggingImage can be set from command line
  • Windows MSVC projects updated to link against OpenCV 2.4.6
  • Fixes for gcc 4.7 (thanks to Sarma Tangirala)
  • Bug fixes and performance improvements

Version 1.6:

  • Changed vision code from OpenCV 1.x C API to OpenCV 2.x C++ API
  • Added drwnHistogram class by Jason Corso
  • Added separate EPSG, EPSF and EPSX parameters to drwnOptimizer and changed signature of solve function
  • Added "-outUnary" option to inferPixelLabels for writing out unary potentials
  • Improved Matlab mex interfaces
  • Added drwnFeatureTransformFactory and improved drwnFactory class
  • Added drwnLinearTransform class
  • Bug fixes and performance improvements

Logo Theano 0.6

by jaberg - December 3, 2013, 20:32:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12184 views, 2289 downloads, 1 subscription

About: A Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Dynamically generates CPU and GPU modules for good performance. Deep Learning Tutorials illustrate deep learning with Theano.

Changes:

Theano 0.6 (December 3th, 2013)

Highlight:

* Last release with support for Python 2.4 and 2.5.
* We will try to release more frequently.
* Fix crash/installation problems.
* Use less memory for conv3d2d.

0.6rc4 skipped for a technical reason.

Highlights (since 0.6rc3):

* Python 3.3 compatibility with buildbot test for it.
* Full advanced indexing support.
* Better Windows 64 bit support.
* New profiler.
* Better error messages that help debugging.
* Better support for newer NumPy versions (remove useless warning/crash).
* Faster optimization/compilation for big graph.
* Move in Theano the Conv3d2d implementation.
* Better SymPy/Theano bridge: Make an Theano op from SymPy expression and use SymPy c code generator.
* Bug fixes.

Too much changes in 0.6rc1, 0.6rc2 and 0.6rc3 to list here. See https://github.com/Theano/Theano/blob/master/NEWS.txt for details.


Logo GBAC 0.0.4

by henrydcl - November 22, 2013, 20:04:16 CET [ BibTeX BibTeX for corresponding Paper Download ] 1950 views, 668 downloads, 2 subscriptions

About: Probabilistic performance evaluation for multiclass classification using the posterior balanced accuracy

Changes:

Added bibtex information.


Logo JMLR CAM Java 3.1

by wangny - October 14, 2013, 22:46:03 CET [ Project Homepage BibTeX Download ] 4860 views, 2400 downloads, 1 subscription

About: The CAM R-Java software provides a noval way to solve blind source separation problem.

Changes:

In this version, we fix the problem of not working under newest R version R-3.0.


Logo RLPy 1.2

by bobklein2 - October 9, 2013, 03:33:43 CET [ Project Homepage BibTeX Download ] 1198 views, 271 downloads, 1 subscription

About: RLPy is a framework for performing reinforcement learning (RL) experiments in Python. RLPy provides a large library of agent and domain components, and a suite of tools to aid in experiments (parallelization, hyperparameter optimization, code profiling, and plotting).

Changes:

Initial Announcement on mloss.org.


Logo Multilinear Principal Component Analysis 1.3

by hplu - September 8, 2013, 13:04:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3439 views, 662 downloads, 1 subscription

About: A Matlab implementation of Multilinear PCA (MPCA) and MPCA+LDA for dimensionality reduction of tensor data with sample code on gait recognition

Changes:
  1. The MPCA paper is updated with a typo (the MAD measure in Table II) corrected.

  2. Tensor toolbox version 2.1 is included for convenience.

  3. Full code on gait recognition is included for verification and comparison.


Logo CIlib Computational Intelligence Library 0.8

by gpampara - August 22, 2013, 08:34:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1040 views, 287 downloads, 1 subscription

About: CIlib is a library of computational intelligence algorithms and supporting components that allows simple extension and experimentation. The library is peer reviewed and is backed by a leading research group in the field. The library is under active development.

Changes:

Initial Announcement on mloss.org.


Logo Nonparametric Sparse Factor Analysis 1

by davidknowles - July 26, 2013, 01:02:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1203 views, 261 downloads, 1 subscription

About: This is the core MCMC sampler for the nonparametric sparse factor analysis model presented in David A. Knowles and Zoubin Ghahramani (2011). Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling. Annals of Applied Statistics

Changes:

Initial Announcement on mloss.org.


Logo ClusterEval 1.0

by cdevries - June 16, 2013, 04:15:30 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1314 views, 454 downloads, 1 subscription

About: Cluster quality Evaluation software. Implements cluster quality metrics based on ground truths such as Purity, Entropy, Negentropy, F1 and NMI. It includes a novel approach to correct for pathological or ineffective clusterings called 'Divergence from a Random Baseline'.

Changes:

Initial Announcement on mloss.org.


Logo AISAIC 1.0.0610

by fydennis - June 13, 2013, 21:54:55 CET [ BibTeX Download ] 1194 views, 762 downloads, 1 subscription

About: AISAIC software for analyzing human DNA copy numbers and detecting significant copy number alterations

Changes:

Initial Announcement on mloss.org.


Logo Cognitive Foundry 3.3.3

by Baz - May 21, 2013, 05:59:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15405 views, 2440 downloads, 2 subscriptions

About: The Cognitive Foundry is a modular Java software library of machine learning components and algorithms designed for research and applications.

Changes:
  • General:
    • Made code able to compile under both Java 1.6 and 1.7. This required removing some potentially unsafe methods that used varargs with generics.
    • Upgraded XStream dependency to 1.4.4.
    • Improved support for regression algorithms in learning.
    • Added general-purpose adapters to make it easier to compose learning algorithms and adapt their input or output.
  • Common Core:
    • Added isSparse, toArray, dotDivide, and dotDivideEquals methods for Vector and Matrix.
    • Added scaledPlus, scaledPlusEquals, scaledMinus, and scaledMinusEquals to Ring (and thus Vector and Matrix) for potentially faster such operations.
    • Fixed issue where matrix and dense vector equals was not checking for equal dimensionality.
    • Added transform, transformEquals, tranformNonZeros, and transformNonZerosEquals to Vector.
    • Made LogNumber into a signed version of a log number and moved the prior unsigned implementation into UnsignedLogNumber.
    • Added EuclideanRing interface that provides methods for times, timesEquals, divide, and divideEquals. Also added Field interface that provides methods for inverse and inverseEquals. These interfaces are now implemented by the appropriate number classes such as ComplexNumber, MutableInteger, MutableLong, MutableDouble, LogNumber, and UnsignedLogNumber.
    • Added interface for Indexer and DefaultIndexer implementation for creating a zero-based indexing of values.
    • Added interfaces for MatrixFactoryContainer and DivergenceFunctionContainer.
    • Added ReversibleEvaluator, which various identity functions implement as well as a new utility class ForwardReverseEvaluatorPair to create a reversible evaluator from a pair of other evaluators.
    • Added method to create an ArrayList from a pair of values in CollectionUtil.
    • ArgumentChecker now properly throws assertion errors for NaN values. Also added checks for long types.
    • Fixed handling of Infinity in subtraction for LogMath.
    • Fixed issue with angle method that would cause a NaN if cosine had a rounding error.
    • Added new createMatrix methods to MatrixFactory that initializes the Matrix with the given value.
    • Added copy, reverse, and isEmpty methods for several array types to ArrayUtil.
    • Added utility methods for creating a HashMap, LinkedHashMap, HashSet, or LinkedHashSet with an expected size to CollectionUtil.
    • Added getFirst and getLast methods for List types to CollectionUtil.
    • Removed some calls to System.out and Exception.printStackTrace.
  • Common Data:
    • Added create method for IdentityDataConverter.
    • ReversibleDataConverter now is an extension of ReversibleEvaluator.
  • Learning Core:
    • Added general learner transformation capability to make it easier to adapt and compose algorithms. InputOutputTransformedBatchLearner provides this capability for supervised learning algorithms by composing together a triplet. CompositeBatchLearnerPair does it for a pair of algorithms.
    • Added a constant and identity learners.
    • Added Chebyshev, Identity, and Minkowski distance metrics.
    • Added methods to DatasetUtil to get the output values for a dataset and to compute the sum of weights.
    • Made generics more permissive for supervised cost functions.
    • Added ClusterDistanceEvaluator for taking a clustering that encodes the distance from an input value to all clusters and returns the result as a vector.
    • Fixed potential round-off issue in decision tree splitter.
    • Added random subspace technique, implemented in RandomSubspace.
    • Separated functionality from LinearFunction into IdentityScalarFunction. LinearFunction by default is the same, but has parameters that can change the slope and offset of the function.
    • Default squashing function for GeneralizedLinearModel and DifferentiableGeneralizedLinearModel is now a linear function instead of an atan function.
    • Added a weighted estimator for the Poisson distribution.
    • Added Regressor interface for evaluators that are the output of (single-output) regression learning algorithms. Existing such evaluators have been updated to implement this interface.
    • Added support for regression ensembles including additive and averaging ensembles with and without weights. Added a learner for regression bagging in BaggingRegressionLearner.
    • Added a simple univariate regression class in UnivariateLinearRegression.
    • MultivariateDecorrelator now is a VectorInputEvaluator and VectorOutputEvaluator.
    • Added bias term to PrimalEstimatedSubGradient.
  • Text Core:
    • Fixed issue with the start position for tokens from LetterNumberTokenizer being off by one except for the first one.

Logo HLearn 1.0

by mikeizbicki - May 9, 2013, 05:58:18 CET [ Project Homepage BibTeX Download ] 2384 views, 542 downloads, 1 subscription

About: HLearn makes simple machine learning routines available in Haskell by expressing them according to their algebraic structure

Changes:

Updated to version 1.0


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