Projects supporting the bin data format.


Logo JMLR MLPACK 1.0.9

by rcurtin - July 28, 2014, 20:52:10 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 30799 views, 6192 downloads, 6 subscriptions

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About: A scalable, fast C++ machine learning library, with emphasis on usability.

Changes:
  • GMM initialization is now safer and provides a working GMM when constructed with only the dimensionality and number of Gaussians (#314).
  • Check for division by 0 in Forward-Backward Algorithm in HMMs (#314).
  • Fix MaxVarianceNewCluster (used when re-initializing clusters for k-means) (#314).
  • Fixed implementation of Viterbi algorithm in HMM::Predict() (#316).
  • Significant speedups for dual-tree algorithms using the cover tree (#243, #329) including a faster implementation of FastMKS.
  • Fix for LRSDP optimizer so that it compiles and can be used (#325).
  • CF (collaborative filtering) now expects users and items to be zero-indexed, not one-indexed (#324).
  • CF::GetRecommendations() API change: now requires the number of recommendations as the first parameter. The number of users in the local neighborhood should be specified with CF::NumUsersForSimilarity().
  • Removed incorrect PeriodicHRectBound (#30).
  • Refactor LRSDP into LRSDP class and standalone function to be optimized (#318).
  • Fix for centering in kernel PCA (#355).
  • Added simulated annealing (SA) optimizer, contributed by Zhihao Lou.
  • HMMs now support initial state probabilities; these can be set in the constructor, trained, or set manually with HMM::Initial() (#315).
  • Added Nyström method for kernel matrix approximation by Marcus Edel.
  • Kernel PCA now supports using Nyström method for approximation.
  • Ball trees now work with dual-tree algorithms, via the BallBound<> bound structure (#320); fixed by Yash Vadalia.
  • The NMF class is now AMF<>, and supports far more types of factorizations, by Sumedh Ghaisas.
  • A QUIC-SVD implementation has returned, written by Siddharth Agrawal and based on older code from Mudit Gupta.
  • Added perceptron and decision stump by Udit Saxena (these are weak learners for an eventual AdaBoost class).
  • Sparse autoencoder added by Siddharth Agrawal.

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 Divvy 1.1.1

by jlewis - November 14, 2012, 20:21:29 CET [ Project Homepage BibTeX Download ] 1474 views, 735 downloads, 1 subscription

About: Divvy is a Mac OS X application for performing dimensionality reduction, clustering, and visualization.

Changes:

Initial Announcement on mloss.org.


Logo sccan 0.0

by stnava - January 13, 2011, 18:14:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3215 views, 787 downloads, 1 subscription

About: A work in progress

Changes:

Initial Announcement on mloss.org.


Logo ELF Ensemble Learning Framework 0.1

by mjahrer - May 10, 2010, 23:54:53 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4685 views, 774 downloads, 1 subscription

About: ELF provides many well implemented supervised learners for classification and regression tasks with an opportunity of ensemble learning.

Changes:

Initial Announcement on mloss.org.