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Showing Items 41-50 of 626 on page 5 of 63: Previous 1 2 3 4 5 6 7 8 9 10 Next Last

Logo r-cran-CoxBoost 1.4

by r-cran-robot - October 1, 2016, 00:00:04 CET [ Project Homepage BibTeX Download ] 29152 views, 5678 downloads, 3 subscriptions

About: Cox models by likelihood based boosting for a single survival endpoint or competing risks


Fetched by r-cran-robot on 2016-10-01 00:00:04.178988

Logo MIToolbox 2.1.2

by apocock - January 10, 2016, 22:19:30 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 28284 views, 4839 downloads, 2 subscriptions

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.


Relicensed as BSD. Added checks to catch MATLAB inputs that aren't doubles.

Logo r-cran-RWeka 0.4-10

by r-cran-robot - January 10, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 27798 views, 6100 downloads, 1 subscription

About: R/Weka interface


Fetched by r-cran-robot on 2012-02-01 00:00:11.330277

Logo JMLR pebl Python Environment for Bayesian Learning 1.0.1

by abhik - March 5, 2009, 00:05:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 27629 views, 2937 downloads, 1 subscription

About: Pebl is a python library and command line application for learning the structure of a Bayesian network given prior knowledge and observations.


Updated version to 1.0.1

Logo JMLR LPmade 1.2.2

by rlichten - April 2, 2012, 17:11:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 27512 views, 9373 downloads, 1 subscription

About: Link Prediction Made Easy



  • Fixed MAJOR issue related to github migration several months ago. The original github commit neglected to import empty folders. This caused parts of the project compilation procedure to fail. Any users of LPmade who downloaded the most recent version from github over the last several months would have encountered this build error and should download the most recent version. This change updates the network library makefile to create the empty folders and gets around the issue. Very sorry to anybody that this may have inconvenienced, but thanks for hanging in there if you diagnosed and solved it yourself.

  • Fixed issue with auroc on 32-bit architectures that caused integer wraparounds that produced incorrect results.

Logo Theano 0.8.1

by jaberg - April 1, 2016, 19:22:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 27361 views, 4634 downloads, 3 subscriptions

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.


Theano 0.8.1 (29th of March, 2016)

* Fix compilation on Mac with CLT 7.3

Theano 0.8 (21th of March, 2016)

We recommend to everyone to upgrade to this version.


* Python 2 and 3 support with the same code base
* Faster optimization
* Integration of CuDNN for better GPU performance
* Many Scan improvements (execution speed up, ...)
* optimizer=fast_compile moves computation to the GPU.
* Better convolution on CPU and GPU. (CorrMM, cudnn, 3d conv, more parameter)
* Interactive visualization of graphs with d3viz
* cnmem (better memory management on GPU)
* BreakpointOp
* Multi-GPU for data parallism via Platoon (
* More pooling parameter supported
* Bilinear interpolation of images
* New GPU back-end:

    * Float16 new back-end (need cuda 7.5)
    * Multi dtypes
    * Multi-GPU support in the same process

Logo peewit 0.10

by lorenz - May 7, 2014, 16:04:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 26650 views, 5191 downloads, 1 subscription

About: peewit provides services for programming, running and result examination of machine learning experiments. It does not include any ML algorithms, has no GUI, and presumes certain uniformity of the experimental layout. But it does not make assumptions on the type of task under study. The current version-number is 0.10.


v-cube with side-cubes

Logo BayesOpt, a Bayesian Optimization toolbox 0.8.2

by rmcantin - December 9, 2015, 04:53:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 26421 views, 4965 downloads, 4 subscriptions

About: BayesOpt is an efficient, C++ implementation of the Bayesian optimization methodology for nonlinear-optimization, experimental design and stochastic bandits. In the literature it is also called Sequential Kriging Optimization (SKO) or Efficient Global Optimization (EGO). There are also interfaces for C, Matlab/Octave and Python.


-Fixed bug in save/restore. -Fixed bug in initial design.

About: The CTBN-RLE is a C++ package of executables and libraries for inference and learning algorithms for continuous time Bayesian networks (CTBNs).


compilation problems fixed

Logo JMLR Mulan 1.5.0

by lefman - February 23, 2015, 21:19:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 25744 views, 8300 downloads, 2 subscriptions

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.



  • Added the MLCSSP algorithm (from ICML 2013)
  • Enhancements of multi-target regression capabilities
  • Improved CLUS support
  • Added pairwise classifier and pairwise transformation


  • Providing training data in the Evaluator is unnecessary in the case of specific measures.
  • Examples with missing ground truth are not skipped for measures that handle missing values.
  • Added logistics and squared error losses and measures

Bug fixes

  • IndexOutOfBounds in calculation of MiAP and GMiAP
  • Bug fix in
  • When in rank/score mode the meta-data contained additional unecessary attributes. (Newton Spolaor)

API changes

  • Upgrade to Java 7
  • Upgrade to Weka 3.7.10


  • Small changes and improvements in the wrapper classes for the CLUS library
  • (new experiment)
  • Enumeration is now used for specifying the type of meta-data. (Newton Spolaor)

Showing Items 41-50 of 626 on page 5 of 63: Previous 1 2 3 4 5 6 7 8 9 10 Next Last