20 projects found that use c as the programming language.
Showing Items 41-60 of 94 on page 3 of 5: Previous 1 2 3 4 5 Next

About: Infrastructure for representing, manipulating and analyzing transaction data and frequent patterns.

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 ] 3292 views, 657 downloads, 1 subscription

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

Changes:

Initial Announcement on mloss.org.


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 ] 29505 views, 5430 downloads, 1 subscription

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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)

Logo Scilab Pattern Recognition Toolbox 0.0.2

by openpr_nlpr - December 2, 2011, 04:27:49 CET [ Project Homepage BibTeX Download ] 1232 views, 328 downloads, 1 subscription

About: Scilab Pattern Recognition Toolbox is a toolbox developed for Scilab software, and is used in pattern recognition, machine learning and the related field. It is developed for the purpose of education and research.

Changes:

Initial Announcement on mloss.org.


Logo GraphLab v1-1908

by dannybickson - November 22, 2011, 12:50:00 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4395 views, 757 downloads, 1 subscription

About: Multicore/distributed large scale machine learning framework.

Changes:

Update version.


About: FLANN is a library for performing fast approximate nearest neighbor searches in high dimensional spaces. It contains a collection of algorithms we found to work best for nearest neighbor search.

Changes:

See project page for changes.


Logo GritBot 2.01

by zenog - September 2, 2011, 14:56:26 CET [ Project Homepage BibTeX Download ] 2259 views, 556 downloads, 1 subscription

About: GritBot is an data cleaning and outlier/anomaly detection program.

Changes:

Initial Announcement on mloss.org.


Logo Cubist 2.07

by zenog - September 2, 2011, 14:52:17 CET [ Project Homepage BibTeX Download ] 2330 views, 609 downloads, 1 subscription

About: Cubist is the regression counterpart to the C5.0 decision tree tool.

Changes:

Initial Announcement on mloss.org.


Logo C5.0 2.07

by zenog - September 2, 2011, 14:49:04 CET [ Project Homepage BibTeX Download ] 2541 views, 640 downloads, 1 subscription

About: C5.0 is the successor of the C4.5 decision tree algorithm/tool. In particular, it is faster and more memory-efficient.

Changes:

Initial Announcement on mloss.org.


Logo K tree 0.4.2

by cdevries - July 4, 2011, 06:01:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5925 views, 1302 downloads, 1 subscription

About: The K-tree is a scalable approach to clustering inspired by the B+-tree and k-means algorithms.

Changes:

Release of K-tree implementation in Python. This is targeted at a research and rapid prototyping audience.


Logo 1SpectralClustering 1.1

by tbuehler - June 27, 2011, 10:45:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6956 views, 1323 downloads, 1 subscription

About: A fast and scalable graph-based clustering algorithm based on the eigenvectors of the nonlinear 1-Laplacian.

Changes:
  • fixed bug occuring when input graph is disconnected
  • reduced memory usage when input graph has large number of disconnected components
  • more user-friendly usage of main method OneSpectralClustering
  • faster computation of eigenvector initialization + now thresholded according to multicut-criterion
  • several internal optimizations

Logo NetPro 1.1.17

by lml - January 25, 2011, 19:02:53 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3315 views, 787 downloads, 1 subscription

About: Tools for functional network analysis.

Changes:

Initial Announcement on mloss.org.


Logo scikits.learn 0.6

by fabianp - December 22, 2010, 11:58:30 CET [ Project Homepage BibTeX Download ] 6543 views, 1208 downloads, 1 subscription

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About: Obsolete. Use https://mloss.org/software/view/240/ instead.

Changes:

0.6 release


Logo LIBOCAS 0.93

by vf - June 20, 2010, 12:22:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9458 views, 1410 downloads, 2 subscriptions

About: The library implements Optimized Cutting Plane Algorithm (OCAS) for efficient training of linear SVM classifiers from large-scale data.

Changes:

Implemented COFFIN framework which allows efficient training of invariant image classifiers via virtual examples.


Logo dANN AI Library 1.3

by freemo - April 25, 2010, 05:36:46 CET [ Project Homepage BibTeX Download ] 4132 views, 1009 downloads, 1 subscription

About: dANN is an Artificial Intelligence and Artificial Genetics library targeted at employing conventional techniques as well as acting as a platform for research & development of novel techniques. As new techniques are developed and proven to be effective they will be integrated into the core library. It is currently written in Java, C++, and C#. However only the java version is currently in active development. If you want to obtain a version other than the java version you will need to get it directly from GIT.

Changes:

Please get the version in GIT only, the released version is old.


Logo Bilingual Text Classification 0.1

by jorcisai - April 9, 2010, 15:13:08 CET [ BibTeX BibTeX for corresponding Paper Download ] 2494 views, 908 downloads, 1 subscription

About: This software package implements a series of statistical mixture models for bilingual text classificacion trained by the EM algorihtm.

Changes:

Initial Announcement on mloss.org.


Logo The GIDOC prototype 1.1

by nserrano - April 9, 2010, 12:57:00 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5171 views, 836 downloads, 1 subscription

About: GIDOC (Gimp-based Interactive transcription of old text DOCuments) is a computer-assisted transcription prototype for handwritten text in old documents. It is a first attempt to provide integrated support for interactive-predictive page layout analysis, text line detection and handwritten text transcription. GIDOC is built on top of the well-known GNU Image Manipulation Program (GIMP), and uses standard techniques and tools for handwritten text preprocessing and feature extraction, HMM-based image modelling, and language modelling.

Changes:

Updated version for mloss 2010


Logo FWTN 1.0

by hn - March 25, 2010, 16:58:24 CET [ Project Homepage BibTeX Download ] 3870 views, 855 downloads, 1 subscription

About: Orthonormal wavelet transform for D dimensional tensors in L levels. Generic quadrature mirror filters and tensor sizes. Runtime is O(n), plain C, MEX-wrapper and demo provided.

Changes:

Initial Announcement on mloss.org.


Logo LIBSVM 2.9

by cjlin - February 27, 2010, 01:09:23 CET [ Project Homepage BibTeX Download ] 10558 views, 2158 downloads, 1 subscription

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About: LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC ), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class [...]

Changes:

Initial Announcement on mloss.org.


Logo svmPRAT 1.0

by rangwala - December 28, 2009, 00:27:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3734 views, 927 downloads, 1 subscription

About: BACKGROUND:Over the last decade several prediction methods have been developed for determining the structural and functional properties of individual protein residues using sequence and sequence-derived information. Most of these methods are based on support vector machines as they provide accurate and generalizable prediction models. RESULTS:We present a general purpose protein residue annotation toolkit (svmPRAT) to allow biologists to formulate residue-wise prediction problems. svmPRAT formulates the annotation problem as a classification or regression problem using support vector machines. One of the key features of svmPRAT is its ease of use in incorporating any user-provided information in the form of feature matrices. For every residue svmPRAT captures local information around the reside to create fixed length feature vectors. svmPRAT implements accurate and fast kernel functions, and also introduces a flexible window-based encoding scheme that accurately captures signals and pattern for training eective predictive models. CONCLUSIONS:In this work we evaluate svmPRAT on several classification and regression problems including disorder prediction, residue-wise contact order estimation, DNA-binding site prediction, and local structure alphabet prediction. svmPRAT has also been used for the development of state-of-the-art transmembrane helix prediction method called TOPTMH, and secondary structure prediction method called YASSPP. This toolkit developed provides practitioners an efficient and easy-to-use tool for a wide variety of annotation problems. Availability: http://www.cs.gmu.edu/~mlbio/svmprat/

Changes:

Initial Announcement on mloss.org.


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