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Showing Items 111-120 of 622 on page 12 of 63: First Previous 7 8 9 10 11 12 13 14 15 16 17 Next Last

Logo HSSVM 1.0.1

by xjbean - June 8, 2010, 16:16:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13283 views, 2691 downloads, 1 subscription

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About: HSSVM is a software for solving multi-class problem using Hyper-sphere Support Vector Machines model, implemented by Java.

Changes:
  1. From this version, the version number is normalized to hssvm1.0.1;
  2. In this version, we delete the features about running parameter searching and run-all from Ant script, that is, commands "ant search-param" and "ant run-all" which exist in previous version are no longer available, and they are replaced with commands "svm search conf" and "svm runall conf", both of them are used on Linux(or all other POSIX systems).If you want to use this program on Windows, the cygwin is required to be installed.

Logo LIBSVM 2.9

by cjlin - February 27, 2010, 01:09:23 CET [ Project Homepage BibTeX Download ] 13086 views, 2727 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 r-cran-rgp 0.2-4

by r-cran-robot - April 1, 2013, 00:00:08 CET [ Project Homepage BibTeX Download ] 13036 views, 2263 downloads, 0 subscriptions

About: R genetic programming framework

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:08.163887


Logo KeBABS 1.4.1

by UBod - November 3, 2015, 11:33:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12863 views, 2350 downloads, 3 subscriptions

About: Kernel-Based Analysis of Biological Sequences

Changes:
  • new method to compute prediction profiles from models trained with mixture kernels
  • correction for position specific kernel with offsets
  • corrections for prediction profile of motif kernel
  • additional hint on help page of kbsvm

Logo Torch 5 5.1

by andresy - October 1, 2008, 04:25:12 CET [ Project Homepage BibTeX Download ] 12737 views, 1903 downloads, 2 subscriptions

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About: Torch5 provides a matlab-like environment for state-of-the-art machine learning algorithms. It is easy to use and provides a very efficient implementation, thanks to a easy and fast scripting [...]

Changes:

Initial Announcement on mloss.org.


About: RLLib is a lightweight C++ template library that implements incremental, standard, and gradient temporal-difference learning algorithms in Reinforcement Learning. It is an optimized library for robotic applications and embedded devices that operates under fast duty cycles (e.g., < 30 ms). RLLib has been tested and evaluated on RoboCup 3D soccer simulation agents, physical NAO V4 humanoid robots, and Tiva C series launchpad microcontrollers to predict, control, learn behaviors, and represent learnable knowledge. The implementation of the RLLib library is inspired by the RLPark API, which is a library of temporal-difference learning algorithms written in Java.

Changes:

Current release version is v2.0.


Logo r-cran-svmpath 0.952

by r-cran-robot - February 1, 2012, 00:00:11 CET [ Project Homepage BibTeX Download ] 12636 views, 2637 downloads, 1 subscription

About: svmpath

Changes:

Fetched by r-cran-robot on 2012-02-01 00:00:11.755984


Logo kernlab 0.9-9

by alexis - November 2, 2009, 16:03:50 CET [ Project Homepage BibTeX Download ] 12534 views, 2572 downloads, 0 subscriptions

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About: kernlab provides kernel-based Machine Learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods kernlab [...]

Changes:

minor fixes in kcca and ksvm functions


Logo libnabo 1.0.6

by smagnenat - August 5, 2015, 12:16:40 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12515 views, 2707 downloads, 3 subscriptions

About: libnabo is a fast K Nearset Neighbor library for low-dimensional spaces.

Changes:
  • Reset point indices of results with distances exceeding threshold (#23, #24)
  • Fine tune the find_package() capability and add uninstall target (#22)
  • Fixed compiler warning (#18)
  • Added OpenMP support (#20, #21)
  • Build type tuning (#19)
  • Fix: terminal comma in enum requires C++11
  • Fix UBSAN error calculating maxNodeCount (#16, #17)
  • Fixed tiny (yet significant) error in the Python doc strings (#15)
  • Compile static lib with PIC (#14)
  • Added configure scripts for full catkinization
  • Catkinization of libnabo (following REP136)
  • Update README.md Added Simon as the maintainer.
  • [test] use CLOCK_PROF for NetBSD build
  • Fixed CppCheck warning. Fix broken install when doxygen is not found
  • Fix cmake stylistic issue
  • Make python install respect custom CMAKE_INSTALL_PREFIX
  • Fix broken install when doxygen is not found

Logo JMLR EnsembleSVM 2.0

by claesenm - March 31, 2014, 08:06:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12388 views, 4142 downloads, 2 subscriptions

About: The EnsembleSVM library offers functionality to perform ensemble learning using Support Vector Machine (SVM) base models. In particular, we offer routines for binary ensemble models using SVM base classifiers. Experimental results have shown the predictive performance to be comparable with standard SVM models but with drastically reduced training time. Ensemble learning with SVM models is particularly useful for semi-supervised tasks.

Changes:

The library has been updated and features a variety of new functionality as well as more efficient implementations of original features. The following key improvements have been made:

  1. Support for multithreading in training and prediction with ensemble models. Since both of these are embarassingly parallel, this has induced a significant speedup (3-fold on quad-core).
  2. Extensive programming framework for aggregation of base model predictions which allows highly efficient prototyping of new aggregation approaches. Additionally we provide several predefined strategies, including (weighted) majority voting, logistic regression and nonlinear SVMs of your choice -- be sure to check out the esvm-edit tool! The provided framework also allows you to efficiently program your own, novel aggregation schemes.
  3. Full code transition to C++11, the latest C++ standard, which enabled various performance improvements. The new release requires moderately recent compilers, such as gcc 4.7.2+ or clang 3.2+.
  4. Generic implementations of convenient facilities have been added, such as thread pools, deserialization factories and more.

The API and ABI have undergone significant changes, many of which are due to the transition to C++11.


Showing Items 111-120 of 622 on page 12 of 63: First Previous 7 8 9 10 11 12 13 14 15 16 17 Next Last