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Logo JMLR Jstacs 2.1

by keili - June 3, 2013, 07:32:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13271 views, 3108 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 JMLR Mulan 1.4.0

by lefman - August 1, 2012, 09:49:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13165 views, 5656 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 r-cran-e1071 1.6-3

by r-cran-robot - February 13, 2014, 00:00:00 CET [ Project Homepage BibTeX Download ] 12636 views, 2631 downloads, 1 subscription

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About: Misc Functions of the Department of Statistics (e1071), TU Wien

Changes:

Fetched by r-cran-robot on 2014-07-01 00:00:05.706563


Logo r-cran-arules 1.1-3

by r-cran-robot - June 17, 2014, 00:00:00 CET [ Project Homepage BibTeX Download ] 12493 views, 2582 downloads, 2 subscriptions

About: Mining Association Rules and Frequent Itemsets

Changes:

Fetched by r-cran-robot on 2014-07-01 00:00:03.926443


Logo Theano 0.6

by jaberg - December 3, 2013, 20:32:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12131 views, 2285 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 JMLR Model Monitor 1.0

by traeder - August 17, 2009, 11:05:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12124 views, 1683 downloads, 0 comments, 1 subscription

About: Model Monitor is a Java toolkit for the systematic evaluation of classifiers under changes in distribution. It provides methods for detecting distribution shifts in data, comparing the performance [...]

Changes:

Improved AUROC calculation. Several minor bug fixes.


Logo DAL 1.1

by ryota - February 18, 2014, 19:07:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12109 views, 2116 downloads, 1 subscription

About: DAL is an efficient and flexibible MATLAB toolbox for sparse/low-rank learning/reconstruction based on the dual augmented Lagrangian method.

Changes:
  • Supports weighted lasso (dalsqal1.m, dallral1.m)
  • Supports weighted squared loss (dalwl1.m)
  • Bug fixes (group lasso and elastic-net-regularized logistic regression)

About: This toolbox provides functions for maximizing and minimizing submodular set functions, with applications to Bayesian experimental design, inference in Markov Random Fields, clustering and others.

Changes:
  • Modified specification of optional parameters (using sfo_opt)
  • Added sfo_ls_lazy for maximizing nonnegative submodular functions
  • Added sfo_fn_infogain, sfo_fn_lincomb, sfo_fn_invert, ...
  • Added additional documentation and more examples
  • Now Octave ready

Logo JMLR JNCC2 1.11

by gcorani - January 1, 2009, 03:22:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11900 views, 1423 downloads, 0 comments, 1 subscription

About: JNCC2 is the open-source implementation of the Naive Credal Classifier2 (NCC2), i.e., an extension of Naive Bayes towards imprecise probabilities, designed to deliver robust classifications even on [...]

Changes:

Initial Announcement on mloss.org.


Logo MIToolbox 2.1

by apocock - June 30, 2014, 01:05:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11801 views, 2264 downloads, 1 subscription

About: A mutual information library for C and Mex bindings for MATLAB. Aimed at feature selection, and provides simple methods to calculate mutual information, conditional mutual information, entropy, conditional entropy, Renyi entropy/mutual information, and weighted variants of Shannon entropies/mutual informations. Works with discrete distributions, and expects column vectors of features.

Changes:

Added weighted entropy functions. Fixed a few memory handling bugs.


Showing Items 61-70 of 535 on page 7 of 54: First Previous 2 3 4 5 6 7 8 9 10 11 12 Next Last