Projects that are tagged with classification.
Showing Items 21-40 of 75 on page 2 of 4: Previous 1 2 3 4 Next

Logo RankSVM NC 1.0

by rflamary - July 10, 2014, 15:51:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2043 views, 522 downloads, 1 subscription

About: This package is an implementation of a linear RankSVM solver with non-convex regularization.

Changes:

Initial Announcement on mloss.org.


Logo JMLR MOA Massive Online Analysis Nov-13

by abifet - April 4, 2014, 03:50:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14168 views, 5480 downloads, 1 subscription

About: Massive Online Analysis (MOA) is a real time analytic tool for data streams. It is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collection of offline and online methods as well as tools for evaluation. In particular, it implements boosting, bagging, and Hoeffding Trees, all with and without Naive Bayes classifiers at the leaves. MOA supports bi-directional interaction with WEKA, the Waikato Environment for Knowledge Analysis, and it is released under the GNU GPL license.

Changes:

New version November 2013


Logo JMLR EnsembleSVM 2.0

by claesenm - March 31, 2014, 08:06:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8527 views, 3051 downloads, 2 subscriptions

About: The EnsembleSVM library offers functionality to perform ensemble learning using Support Vector Machine (SVM) base models. In particular, we offer routines for binary ensemble models using SVM base classifiers. Experimental results have shown the predictive performance to be comparable with standard SVM models but with drastically reduced training time. Ensemble learning with SVM models is particularly useful for semi-supervised tasks.

Changes:

The library has been updated and features a variety of new functionality as well as more efficient implementations of original features. The following key improvements have been made:

  1. Support for multithreading in training and prediction with ensemble models. Since both of these are embarassingly parallel, this has induced a significant speedup (3-fold on quad-core).
  2. Extensive programming framework for aggregation of base model predictions which allows highly efficient prototyping of new aggregation approaches. Additionally we provide several predefined strategies, including (weighted) majority voting, logistic regression and nonlinear SVMs of your choice -- be sure to check out the esvm-edit tool! The provided framework also allows you to efficiently program your own, novel aggregation schemes.
  3. Full code transition to C++11, the latest C++ standard, which enabled various performance improvements. The new release requires moderately recent compilers, such as gcc 4.7.2+ or clang 3.2+.
  4. Generic implementations of convenient facilities have been added, such as thread pools, deserialization factories and more.

The API and ABI have undergone significant changes, many of which are due to the transition to C++11.


Logo Malheur 0.5.4

by konrad - December 25, 2013, 13:20:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15296 views, 2935 downloads, 1 subscription

About: Automatic Analysis of Malware Behavior using Machine Learning

Changes:

Support for new version of libarchive. Minor bug fixes.


Logo Gesture Recogition Toolkit 0.1 Revision 289

by ngillian - December 13, 2013, 22:59:53 CET [ Project Homepage BibTeX Download ] 5289 views, 1000 downloads, 1 subscription

About: The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library that has been specifically designed for real-time gesture recognition. It features a large number of machine-learning algorithms for both classification and regression in addition to a wide range of supporting algorithms for pre-processing, feature extraction and dataset management. The GRT has been designed for real-time gesture recognition, but it can also be applied to more general machine-learning tasks.

Changes:

Added Decision Tree and Random Forests.


Logo LIBOL 0.3.0

by stevenhoi - December 12, 2013, 15:26:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11463 views, 4095 downloads, 2 subscriptions

About: LIBOL is an open-source library with a family of state-of-the-art online learning algorithms for machine learning and big data analytics research. The current version supports 16 online algorithms for binary classification and 13 online algorithms for multiclass classification.

Changes:

In contrast to our last version (V0.2.3), the new version (V0.3.0) has made some important changes as follows:

• Add a template and guide for adding new algorithms;

• Improve parameter settings and make documentation clear;

• Improve documentation on data formats and key functions;

• Amend the "OGD" function to use different loss types;

• Fixed some name inconsistency and other minor bugs.


Logo Apache Mahout 0.8

by gsingers - July 27, 2013, 15:52:32 CET [ Project Homepage BibTeX Download ] 17619 views, 4709 downloads, 2 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 [...]

Changes:

Apache Mahout 0.8 contains, amongst a variety of performance improvements and bug fixes, an implementation of Streaming K-Means, deeper Lucene/Solr integration and new scalable recommender algorithms. For a full description of the newest release, see http://mahout.apache.org/.


Logo JMLR Jstacs 2.1

by keili - June 3, 2013, 07:32:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 17481 views, 4188 downloads, 2 subscriptions

About: A Java framework for statistical analysis and classification of biological sequences

Changes:

New classes:

  • MultipleIterationsCondition: Requires another TerminationCondition to fail a contiguous, specified number of times
  • ClassifierFactory: Allows for creating standard classifiers
  • SeqLogoPlotter: Plot PNG sequence logos from within Jstacs
  • MultivariateGaussianEmission: Multivariate Gaussian emission density for a Hidden Markov Model
  • MEManager: Maximum entropy model

New features and improvements:

  • Alignment: Added free shift alignment
  • PerformanceMeasure and sub-classes: Extension to weighted test data
  • AbstractClassifier, ClassifierAssessment and sub-classes: Adaption to weighted PerformanceMeasures
  • DNAAlphabet: Parser speed-up
  • PFMComparator: Extension to PFM from other sources/databases
  • ToolBox: New convenience methods for computing several statistics (e.g., median, correlation)
  • SignificantMotifOccurrencesFinder: New methods for computing PWMs and statistics from predictions
  • SequenceScore and sub-classes: New method toString(NumberFormat)
  • DataSet: Adaption to weighted data, e.g., partitioning
  • REnvironment: Changed several methods from String to CharSequence

Restructuring:

  • changed MultiDimensionalSequenceWrapperDiffSM to MultiDimensionalSequenceWrapperDiffSS

Several minor new features, bug fixes, and code cleanups


Logo MLDemos 0.5.1

by basilio - March 2, 2013, 16:06:13 CET [ Project Homepage BibTeX Download ] 22385 views, 5156 downloads, 2 subscriptions

About: MLDemos is a user-friendly visualization interface for various machine learning algorithms for classification, regression, clustering, projection, dynamical systems, reward maximisation and reinforcement learning.

Changes:

New Visualization and Dataset Features Added 3D visualization of samples and classification, regression and maximization results Added Visualization panel with individual plots, correlations, density, etc. Added Editing tools to drag/magnet data, change class, increase or decrease dimensions of the dataset Added categorical dimensions (indexed dimensions with non-numerical values) Added Dataset Editing panel to swap, delete and rename dimensions, classes or categorical values Several bug-fixes for display, import/export of data, classification performance

New Algorithms and methodologies Added Projections to pre-process data (which can then be classified/regressed/clustered), with LDA, PCA, KernelPCA, ICA, CCA Added Grid-Search panel for batch-testing ranges of values for up to two parameters at a time Added One-vs-All multi-class classification for non-multi-class algorithms Trained models can now be kept and tested on new data (training on one dataset, testing on another) Added a dataset generator panel for standard toy datasets (e.g. swissroll, checkerboard,...) Added a number of clustering, regression and classification algorithms (FLAME, DBSCAN, LOWESS, CCA, KMEANS++, GP Classification, Random Forests) Added Save/Load Model option for GMMs and SVMs Added Growing Hierarchical Self Organizing Maps (original code by Michael Dittenbach) Added Automatic Relevance Determination for SVM with RBF kernel (Thanks to Ashwini Shukla!)


Logo Orange 2.6

by janez - February 14, 2013, 18:15:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14078 views, 2678 downloads, 1 subscription

Rating Whole StarWhole StarWhole StarWhole StarEmpty Star
(based on 1 vote)

About: Orange is a component-based machine learning and data mining software. It includes a friendly yet powerful and flexible graphical user interface for visual programming. For more advanced use(r)s, [...]

Changes:

The core of the system (except the GUI) no longer includes any GPL code and can be licensed under the terms of BSD upon request. The graphical part remains under GPL.

Changed the BibTeX reference to the paper recently published in JMLR MLOSS.


Logo UniverSVM 1.22

by fabee - October 16, 2012, 11:24:12 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 20759 views, 3110 downloads, 0 subscriptions

About: The UniverSVM is a SVM implementation written in C/C++. Its functionality comprises large scale transduction via CCCP optimization, sparse solutions via CCCP optimization and data-dependent [...]

Changes:

Minor changes: fix bug on set_alphas_b0 function (thanks to Ferdinand Kaiser - ferdinand.kaiser@tut.fi)


Logo Linear SVM with general regularization 1.0

by rflamary - October 5, 2012, 15:34:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3510 views, 976 downloads, 1 subscription

About: This package is an implementation of a linear svm solver with a wide class of regularizations on the svm weight vector (l1, l2, mixed norm l1-lq, adaptive lasso). We provide solvers for the classical single task svm problem and for multi-task with joint feature selection or similarity promoting term.

Changes:

Initial Announcement on mloss.org.


Logo MLWizard 5.2

by remat - July 26, 2012, 15:04:14 CET [ Project Homepage BibTeX Download ] 3763 views, 934 downloads, 1 subscription

About: MLwizard recommends and optimizes classification algorithms based on meta-learning and is a software wizard fully integrated into RapidMiner but can be used as library as well.

Changes:

Faster parameter optimization using genetic algorithm with predefined start population.


Logo MLFlex 02-21-2012-00-12

by srp33 - April 3, 2012, 16:44:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2739 views, 579 downloads, 1 subscription

About: Motivated by a need to classify high-dimensional, heterogeneous data from the bioinformatics domain, we developed ML-Flex, a machine-learning toolbox that enables users to perform two-class and multi-class classification analyses in a systematic yet flexible manner. ML-Flex was written in Java but is capable of interfacing with third-party packages written in other programming languages. It can handle multiple input-data formats and supports a variety of customizations. MLFlex provides implementations of various validation strategies, which can be executed in parallel across multiple computing cores, processors, and nodes. Additionally, ML-Flex supports aggregating evidence across multiple algorithms and data sets via ensemble learning. (See http://jmlr.csail.mit.edu/papers/volume13/piccolo12a/piccolo12a.pdf.)

Changes:

Initial Announcement on mloss.org.


Logo Sparse MultiTask Learning Toolbox 1.2

by rflamary - March 18, 2012, 11:31:00 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4010 views, 985 downloads, 1 subscription

About: This package is a set of Matlab scripts that implements the algorithms described in the submitted paper: "Lp-Lq Sparse Linear and Sparse Multiple Kernel MultiTask Learning".

Changes:

Initial Announcement on mloss.org.


Logo MLPY Machine Learning Py 3.5.0

by albanese - March 15, 2012, 09:52:41 CET [ Project Homepage BibTeX Download ] 58688 views, 10989 downloads, 2 subscriptions

Rating Whole StarWhole StarWhole Star1/2 StarEmpty Star
(based on 3 votes)

About: mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL.

Changes:

New features:

  • LibSvm(): pred_probability() now returns probability estimates; pred_values() added
  • LibLinear(): pred_values() and pred_probability() added
  • dtw_std: squared Euclidean option added
  • LCS for series composed by real values (lcs_real()) added
  • Documentation

Fix:

  • wavelet submodule: cwt(): it returned only real values in morlet and poul
  • IRelief(): remove np. in learn()
  • fix rfe_kfda and rfe_w2 when p=1

Logo Large margin filtering 0.9

by rflamary - February 18, 2012, 15:50:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3395 views, 795 downloads, 1 subscription

About: Matlab SVM toolbox for learning large margin filters in signal or images.

Changes:

Initial Announcement on mloss.org.


Logo BCILAB 1.0-beta

by chkothe - January 6, 2012, 23:47:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4412 views, 916 downloads, 1 subscription

About: MATLAB toolbox for advanced Brain-Computer Interface (BCI) research.

Changes:

Initial Announcement on mloss.org.


Logo Kernel Machine Library 0.2

by pawelm - December 27, 2011, 17:14:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper ] 4600 views, 183 downloads, 1 subscription

About: The Kernel-Machine Library is a free (released under the LGPL) C++ library to promote the use of and progress of kernel machines.

Changes:

Updated mloss entry (minor fixes).


Logo PyMVPA Multivariate Pattern Analysis in Python 2.0.0

by yarikoptic - December 22, 2011, 01:36:32 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 32847 views, 5918 downloads, 1 subscription

Rating Whole StarWhole StarWhole StarWhole StarEmpty Star
(based on 2 votes)

About: Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, [...]

Changes:
  • 2.0.0 (Mon, Dec 19 2011)

This release aggregates all the changes occurred between official releases in 0.4 series and various snapshot releases (in 0.5 and 0.6 series). To get better overview of high level changes see :ref:release notes for 0.5 <chap_release_notes_0.5> and :ref:0.6 <chap_release_notes_0.6> as well as summaries of release candidates below

  • Fixes (23 BF commits)

    • significance level in the right tail was fixed to include the value tested -- otherwise resulted in optimistic bias (or absurdly high significance in improbable case if all estimates having the same value)
    • compatible with the upcoming IPython 0.12 and renamed sklearn (Fixes #57)
    • do not double-train slave classifiers while assessing sensitivities (Fixes #53)
  • Enhancements (30 ENH + 3 NF commits)

    • resolving voting ties in kNN based on mean distance, and randomly in SMLR
    • :class:kNN's ca.estimates now contains dictionaries with votes for each class
    • consistent zscoring in :class:Hyperalignment
  • 2.0.0~rc5 (Wed, Oct 19 2011)

  • Major: to allow easy co-existence of stable PyMVPA 0.4.x, 0.6 development mvpa module was renamed into mod:mvpa2.

  • Fixes

    • compatible with the new Shogun 1.x series
    • compatible with the new h5py 2.x series
    • mvpa-prep-fmri -- various compatibility fixes and smoke testing
    • deepcopying :class:SummaryStatistics during add
  • Enhancements

    • tutorial uses :mod:mvpa2.tutorial_suite now
    • better suppression of R warnings when needed
    • internal attributes of many classes were exposed as properties
    • more unification of __repr__ for many classes
  • 0.6.0~rc4 (Wed, Jun 14 2011)

  • Fixes

    • Finished transition to :mod:nibabel conventions in plot_lightbox
    • Addressed :mod:matplotlib.hist API change
    • Various adjustments in the tests batteries (:mod:nibabel 1.1.0 compatibility, etc)
  • New functionality

    • Explicit new argument flatten to from_wizard -- default behavior changed if mapper was provided as well
  • Enhancements

    • Elaborated __str__ and __repr__ for some Classifiers and Measures
  • 0.6.0~rc3 (Thu, Apr 12 2011)

  • Fixes

    • Bugfixes regarding the interaction of FlattenMapper and BoxcarMapper that affected event-related analyses.
    • Splitter now handles attribute value None for splitting properly.
    • GNBSearchlight handling of
      roi_ids.
    • More robust detection of mod:scikits.learn and :mod:nipy externals.
  • New functionality

    • Added a Repeater node to yield a dataset multiple times and
      Sifter node to exclude some datasets. Consequently, the "nosplitting" mode of Splitter got removed at the same time.
    • :file:tools/niils -- little tool to list details (dimensionality, scaling, etc) of the files in nibabel-supported formats.
  • Enhancements

    • Numerous documentation fixes.
    • Various improvements and increased flexibility of null distribution estimation of Measures.
    • All attribute are now reported in sorted order when printing a dataset.
    • fmri_dataset now also stores the input image type.
    • Crossvalidation can now take a custom Splitter instance. Moreover, the default splitter of CrossValidation is more robust in terms of number and type of created splits for common usage patterns (i.e. together with partitioners).
    • CrossValidation takes any custom Node as errorfx argument.
    • ConfusionMatrix can now be used as an errorfx in Crossvalidation.
    • LOE(ACC): Linear Order Effect in ACC was added to
      ConfusionMatrix to detect trends in performances across splits.
    • A Node s postproc is now accessible as a property.
    • RepeatedMeasure has a new 'concat_as' argument that allows results to be concatenated along the feature axis. The default behavior, stacking as multiple samples, is unchanged.
    • Searchlight now has the ability to mark the center/seed of an ROI in with a feature attribute in the generated datasets.
    • debug takes args parameter for delayed string comprehensions. It should reduce run-time impact of debug() calls in regular, non -O mode of Python operation.
    • String summaries and representations (provided by __str__ and __repr__) were made more exhaustive and more coherent. Additional properties to access initial constructor arguments were added to variety of classes.
  • Internal changes

    • New debug target STDOUT to allow attaching metrics (e.g. traceback, timestamps) to regular output printed to stdout

    • New set of decorators to help with unittests

    • @nodebug to disable specific debug targets for the duration of the test.

    • @reseed_rng to guarantee consistent random data given initial seeding.

    • @with_tempfile to provide a tempfile name which would get removed upon completion (test success or failure)

    • Dropping daily testing of maint/0.5 branch -- RIP.

    • Collection s were provided with adequate (deep|)copy. And Dataset was refactored to use Collection s copy method.

    • update-* Makefile rules automatically should fast-forward corresponding website-updates branch

    • MVPA_TESTS_VERBOSITY controls also :mod:numpy warnings now.

    • Dataset.__array__ provides original array instead of copy (unless dtype is provided)

Also adapts changes from 0.4.6 and 0.4.7 (see corresponding changelogs).

  • 0.6.0~rc2 (Thu, Mar 3 2011)

  • Various fixes in the mvpa.atlas module.

  • 0.6.0~rc1 (Thu, Feb 24 2011)

  • Many, many, many

  • For an overview of the most drastic changes :ref:see constantly evolving release notes for 0.6 <chap_release_notes_0.6>

  • 0.5.0 (sometime in March 2010)

This is a special release, because it has never seen the general public. A summary of fundamental changes introduced in this development version can be seen in the :ref:release notes <chap_release_notes_0.5>.

Most notably, this version was to first to come with a comprehensive two-day workshop/tutorial.

  • 0.4.7 (Tue, Mar 07 2011) (Total: 12 commits)

A bugfix release

  • Fixed

    • Addressed the issue with input NIfTI files having scl_ fields set: it could result in incorrect analyses and map2nifti-produced NIfTI files. Now input files account for scaling/offset if scl_ fields direct to do so. Moreover upon map2nifti, those fields get reset.
    • :file:doc/examples/searchlight_minimal.py - best error is the minimal one
  • Enhancements

    • :class:~mvpa.clfs.gnb.GNB can now tolerate training datasets with a single label
    • :class:~mvpa.clfs.meta.TreeClassifier can have trailing nodes with no classifier assigned
  • 0.4.6 (Tue, Feb 01 2011) (Total: 20 commits)

A bugfix release

  • Fixed (few BF commits):

    • Compatibility with numpy 1.5.1 (histogram) and scipy 0.8.0 (workaround for a regression in legendre)
    • Compatibility with libsvm 3.0
    • :class:~mvpa.clfs.plr.PLR robustification
  • Enhancements

    • Enforce suppression of numpy warnings while running unittests. Also setting verbosity >= 3 enables all warnings (Python, NumPy, and PyMVPA)
    • :file:doc/examples/nested_cv.py example (adopted from 0.5)
    • Introduced base class :class:~mvpa.clfs.base.LearnerError for classifiers' exceptions (adopted from 0.5)
    • Adjusted example data to live upto nibabel's warranty of NIfTI standard-compliance
    • More robust operation of MC iterations -- skip iterations where classifier experienced difficulties and raise an exception (e.g. due to degenerate data)

Showing Items 21-40 of 75 on page 2 of 4: Previous 1 2 3 4 Next