Projects that are tagged with icml2010.


Logo JMLR MultiBoost 1.2.02

by busarobi - March 31, 2014, 16:13:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 21890 views, 3869 downloads, 1 subscription

About: MultiBoost is a multi-purpose boosting package implemented in C++. It is based on the multi-class/multi-task AdaBoost.MH algorithm [Schapire-Singer, 1999]. Basic base learners (stumps, trees, products, Haar filters for image processing) can be easily complemented by new data representations and the corresponding base learners, without interfering with the main boosting engine.

Changes:

Major changes :

  • The “early stopping” feature can now based on any metric output with the --outputinfo command line argument.

  • Early stopping now works with --slowresume command line argument.

Minor fixes:

  • More informative output when testing.

  • Various compilation glitch with recent clang (OsX/Linux).


Logo JMLR SHOGUN 3.2.0

by sonne - February 17, 2014, 20:31:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 82369 views, 11391 downloads, 5 subscriptions

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About: The SHOGUN machine learning toolbox's focus is on large scale learning methods with focus on Support Vector Machines (SVM), providing interfaces to python, octave, matlab, r and the command line.

Changes:

This is mostly a bugfix release:

Features

  • Fully support python3 now
  • Add mini-batch k-means [Parijat Mazumdar]
  • Add k-means++ [Parijat Mazumdar]
  • Add sub-sequence string kernel [lambday]

Bugfixes

  • Compile fixes for upcoming swig3.0
  • Speedup for gaussian process' apply()
  • Improve unit / integration test checks
  • libbmrm uninitialized memory reads
  • libocas uninitialized memory reads
  • Octave 3.8 compile fixes [Orion Poplawski]
  • Fix java modular compile error [Bjoern Esser]

Logo JMLR Mulan 1.4.0

by lefman - August 1, 2012, 09:49:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13376 views, 5710 downloads, 1 subscription

About: Mulan is an open-source Java library for learning from multi-label datasets. Multi-label datasets consist of training examples of a target function that has multiple binary target variables. This means that each item of a multi-label dataset can be a member of multiple categories or annotated by many labels (classes). This is actually the nature of many real world problems such as semantic annotation of images and video, web page categorization, direct marketing, functional genomics and music categorization into genres and emotions.

Changes:

Learners

  • BinaryRelevance.java: improved data handling that avoids copying the entire input space, leading to important speedups in case of large datasets and very large number of labels.
  • RAkEL.java: updated technical information, added a check for the case where the number of labels is less or equal than the size of the subset.
  • MultiLabelKNN.java: now checks whether the number of instances is less than the number of requested nearest neighbors.
  • Addition of AdaBoostMH.java, an explicit implementation of AdaBoost.MH as combination of AdaBoostM1 and IncludeLabelsClassifier.
  • Addition of MLPTO.java, the Multi Label Probabilistic Threshold Optimizer (MLTPTO) thresholding technique.
  • Addition of ApproximateExampleBasedFMeasureOptimizer.java, an approximate method for the maximization of example-based F-measure.

Measures/Evaluation

  • Addition of Specificity measure (example-based, micro/macro label-based)
  • Addition of Mean Average Interpolated Precision (MAiP), Geometric Mean Average Precision (GMAP), Geometric Mean Average Interpolated Precision (GMAiP).
  • New methods for stratified multi-label evaluation.
  • Added support for outputting per label results for all measures that implement the MacroAverageMeasure interface.
  • Simplifying the "strictness" issue of information retrieval measures, by adopting specific assumptions (outlined in the new class InformationRetrievalMeasures.java) to handle special cases, instead of the less clear and useful solution of outputting NaN and the less realistic solution or ignoring special cases.

Bug fixes

  • Bug fix in LabelsBuilder.java.
  • Bug fix in Ranker.java.
  • Bug-fix in ThresholdPrediction.java.
  • Fix for bug occurring when loading the XSD for mulan data outside the command-line environment (e.g. web applications).
  • Javadoc comment updates.

API changes

  • Upgrade to Java 1.6
  • Upgrade to JUnit 4.10
  • Upgrade to Weka 3.7.6.

Miscellaneous

  • Meaningful messages are now shown when a DataLoadException is thrown.
  • PT6(PT6Transformation.java): renamed to IncludeLabelsTransformation.java.
  • MultiLabelInstances now support serialization, as needed by the improved binary relevance transformation.
  • BinaryRelevanceAttributeEvaluator.java: updated according to latest BR improvements.

Logo scikits.learn 0.6

by fabianp - December 22, 2010, 11:58:30 CET [ Project Homepage BibTeX Download ] 6344 views, 1163 downloads, 1 subscription

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

Changes:

0.6 release


Logo jblas 1.1.1

by mikio - September 1, 2010, 13:53:51 CET [ Project Homepage BibTeX Download ] 11349 views, 2815 downloads, 1 subscription

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About: jblas is a fast linear algebra library for Java. jblas is based on BLAS and LAPACK, the de-facto industry standard for matrix computations, and uses state-of-the-art implementations like ATLAS for all its computational routines, making jBLAS very fast.

Changes:

Changes from 1.0:

  • Added singular value decomposition
  • Fixed bug with returning complex values
  • Many other minor improvements

Logo JMLR FastInf 1.0

by arielj - June 4, 2010, 14:04:37 CET [ Project Homepage BibTeX Download ] 7787 views, 2594 downloads, 1 subscription

About: The library is focused on implementation of propagation based approximate inference methods. Also implemented are a clique tree based exact inference, Gibbs sampling, and the mean field algorithm.

Changes:

Initial Announcement on mloss.org.


Logo Dependency modeling toolbox 0.2

by lml - April 30, 2010, 14:38:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6826 views, 1045 downloads, 1 subscription

About: Investigation of dependencies between multiple data sources allows the discovery of regularities and interactions that are not seen in individual data sets. The demand for such methods is increasing with the availability and size of co-occurring observations in computational biology, open data initiatives, and in other domains. We provide practical, open access implementations of general-purpose algorithms that help to realize the full potential of these information sources.

Changes:

Three independent modules (drCCA, pint, MultiWayCCA) have been added.


Logo OpenKernel library 0.1

by allauzen - April 23, 2010, 05:25:20 CET [ Project Homepage BibTeX Download ] 8428 views, 986 downloads, 1 subscription

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About: OpenKernel is a library for creating, combining, learning and using kernels for machine learning applications.

Changes:

Initial Announcement on mloss.org.


Logo yaplf 0.7

by malchiod - April 22, 2010, 11:34:07 CET [ Project Homepage BibTeX Download ] 3186 views, 780 downloads, 1 subscription

About: yaplf (Yet Another Python Learning Framework) is an extensible machine learning framework written in python

Changes:

Initial Announcement on mloss.org.


Logo Bilingual Text Classification 0.1

by jorcisai - April 9, 2010, 15:13:08 CET [ BibTeX BibTeX for corresponding Paper Download ] 2372 views, 872 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 ] 4997 views, 791 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 JMLR PyBrain 0.3

by bayerj - March 3, 2010, 15:00:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14969 views, 1681 downloads, 2 subscriptions

About: PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easy-to-use yet still powerful algorithms for machine learning tasks, including a variety of predefined [...]

Changes:
  • more documentation, including new tutorials
  • new and updated example scripts
  • major restructuring of the reinforcement learning part
  • homogeneous interface for optimization algorithms
  • fast networks (arac) are now in an independent package
  • new algorithms, network structures, tools...

Logo Universal Java Matrix Package 0.2.5

by arndt - February 9, 2010, 15:55:23 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9894 views, 1772 downloads, 1 subscription

About: The Universal Java Matrix Package (UJMP) is a data processing tool for Java. Unlike JAMA and Colt, it supports multi-threading and is therefore much faster on current hardware. It does not only support matrices with double values, but instead handles every type of data as a matrix through a common interface, e.g. CSV files, Excel files, images, WAVE audio files, tables in SQL data bases, and much more.

Changes:

Meta data updated.