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Showing Items 1-10 of 561 on page 1 of 57: 1 2 3 4 5 6 Next Last

Logo Somoclu 1.4.1

by peterwittek - January 28, 2015, 13:19:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5618 views, 1056 downloads, 2 subscriptions

About: Somoclu is a massively parallel implementation of self-organizing maps. It relies on OpenMP for multicore execution, MPI for distributing the workload, and it can be accelerated by CUDA on a GPU cluster. A sparse kernel is also included, which is useful for training maps on vector spaces generated in text mining processes. Apart from a command line interface, Python, R, and MATLAB are supported.

Changes:
  • Better support for ICC.
  • Faster code when compiling with GCC.
  • Building instructions and documentation improved.
  • Bug fixes: portability for R, using native R random number generator.

Logo KeBABS 1.0.3

by UBod - January 28, 2015, 10:19:33 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1312 views, 208 downloads, 1 subscription

About: Kernel-Based Analysis Of Biological Sequences

Changes:
  • extension of function linearKernel to optionally return a sparse kernel matrix
  • new accessor SVindex for class KBModel
  • error correction in subsetting of sparse explicit representation for head / tail
  • error correction of vector length overflow in sparse explicit representation for very large number of sequences in spectrum, gappy pair and motif kernel
  • error correction for training with position specific kernel and computation of feature weights
  • error correction in coercion of kernel to character for distance weighting
  • error correction in subsetting of prediction profile
  • error correction in spectrum, gappy pair and motif kernel for kernel matrix - last feature was missing in kernel value in rare situations
  • error correction and minor C code changes for mismatch kernel
  • check uniqueness of motifs in motif kernel
  • build warnings on Windows removed
  • minor changes in help pages
  • change name of vignette Rnw to lowercase
  • minor changes in vignette

Logo Distributed Frank Wolfe Algorithm 0.02

by alirezabagheri - January 28, 2015, 00:35:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 194 views, 27 downloads, 2 subscriptions

About: Distributed optimization: Support Vector Machines and LASSO regression on distributed data

Changes:

Initial Upload


Logo fertilized forests 1.0beta

by Chrisl_S - January 23, 2015, 16:04:31 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 228 views, 23 downloads, 1 subscription

About: The fertilized forests project has the aim to provide an easy to use, easy to extend, yet fast library for decision forests. It summarizes the research in this field and provides a solid platform to extend it. Offering consistent interfaces to C++, Python and Matlab and being available for all major compilers gives the user high flexibility for using the library.

Changes:

Initial Announcement on mloss.org.


About: Learns dynamic network changes across conditions and visualize the results in Cytoscape.

Changes:

Initial Announcement on mloss.org.


Logo Hub Miner 1.1

by nenadtomasev - January 22, 2015, 16:33:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 828 views, 129 downloads, 1 subscription

About: Hubness-aware Machine Learning for High-dimensional Data

Changes:
  • BibTex support for all algorithm implementations, making all of them easy to reference (via algref package).

  • Two more hubness-aware approaches (meta-metric-learning and feature construction)

  • An implementation of Hit-Miss networks for analysis.

  • Several minor bug fixes.

  • The following instance selection methods were added: HMScore, Carving, Iterative Case Filtering, ENRBF.

  • The following clustering quality indexes were added: Folkes-Mallows, Calinski-Harabasz, PBM, G+, Tau, Point-Biserial, Hubert's statistic, McClain-Rao, C-root-k.

  • Some more experimental scripts have been included.

  • Extensions in the estimation of hubness risk.

  • Alias and weighted reservoir methods for weight-proportional random selection.


Logo XGBoost v0.3.9

by crowwork - January 21, 2015, 19:33:24 CET [ Project Homepage BibTeX Download ] 3816 views, 731 downloads, 2 subscriptions

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily. The newest version of xgboost now supports distributed learning on various platforms such as hadoop, mpi and scales to even larger problems

Changes:

New features in the lastest changes

  • Distributed version that scale xgboost to even larger problems with cluster

  • Feature importance visualization in R module

  • Predict leaf index


Logo Rabit 0.1.0

by crowwork - January 21, 2015, 18:48:46 CET [ Project Homepage BibTeX Download ] 186 views, 29 downloads, 1 subscription

About: rabit (Reliable Allreduce and Broadcast Interface) is a light weight library that provides a fault tolerant interface of Allreduce and Broadcast for portable , scalable and reliable distributed machine learning programs. Rabit programs can run on various platforms such as Hadoop, MPI and no installation is needed. Rabit now support kmeans clustering, and distributed xgboost: an extremely efficient disrtibuted boosted tree(GBDT) toolkit.

Changes:

Initial Announcement on mloss.org.


Logo ExtRESCAL 0.7.2

by nzhiltsov - January 20, 2015, 00:35:15 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3696 views, 676 downloads, 2 subscriptions

About: Scalable tensor factorization

Changes:
  • Improve (speed up) initialization of A by summation

Logo pyGPs 1.3.2

by mn - January 17, 2015, 13:08:43 CET [ Project Homepage BibTeX Download ] 3526 views, 818 downloads, 4 subscriptions

About: pyGPs is a Python package for Gaussian process (GP) regression and classification for machine learning.

Changes:

Changelog pyGPs v1.3.2

December 15th 2014

  • pyGPs added to pip
  • mathematical definitions of kernel functions available in documentation
  • more error message added

Showing Items 1-10 of 561 on page 1 of 57: 1 2 3 4 5 6 Next Last