All entries.
Showing Items 181-190 of 645 on page 19 of 65: First Previous 14 15 16 17 18 19 20 21 22 23 24 Next Last

Logo r-cran-C50 0.1.0-24

by r-cran-robot - March 8, 2015, 00:00:00 CET [ Project Homepage BibTeX Download ] 10085 views, 2264 downloads, 0 subscriptions

About: C5.0 Decision Trees and Rule-Based Models

Changes:

Fetched by r-cran-robot on 2017-07-01 00:00:02.580635


Logo Spider 1.71

by jaseweston - November 19, 2007, 15:51:59 CET [ Project Homepage BibTeX Download ] 7495 views, 2261 downloads, 0 subscriptions

Rating Whole StarWhole StarWhole StarWhole StarEmpty Star
(based on 1 vote)

About: The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be [...]

Changes:

Initial Announcement on mloss.org.


Logo Boosted Decision Trees and Lists 1.0.4

by melamed - July 25, 2014, 23:08:32 CET [ BibTeX Download ] 8075 views, 2260 downloads, 3 subscriptions

About: Boosting algorithms for classification and regression, with many variations. Features include: Scalable and robust; Easily customizable loss functions; One-shot training for an entire regularization path; Continuous checkpointing; much more

Changes:
  • added ElasticNets as a regularization option
  • fixed some segfaults, memory leaks, and out-of-range errors, which were creeping in in some corner cases
  • added a couple of I/O optimizations

Logo LSTM for biological sequence analysis 1.0

by mhex - July 28, 2010, 16:32:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9602 views, 2256 downloads, 1 subscription

Rating Whole StarWhole StarWhole StarWhole StarWhole Star
(based on 1 vote)

About: Implementation of LSTM for biological sequence analysis (classification, regression, motif discovery, remote homology detection). Additionally a LSTM as logistic regression with spectrum kernel is included.

Changes:

Spectrum LSTM package included


Logo Easysvm 0.3

by gxr - June 25, 2009, 18:33:04 CET [ Project Homepage BibTeX Download ] 11095 views, 2251 downloads, 1 subscription

About: The Easysvm package provides a set of tools based on the Shogun toolbox allowing to train and test SVMs in a simple way.

Changes:

Fixes for shogun 0.7.3.


Logo SVQP 2

by leonbottou - January 31, 2009, 14:22:04 CET [ Project Homepage BibTeX Download ] 6803 views, 2228 downloads, 0 subscriptions

About: SVQP1 and SVQP2 are QP solvers for training SVM.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-lasso2 1.2-14

by r-cran-robot - November 20, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 10468 views, 2209 downloads, 1 subscription

About: L1 constrained estimation aka `lasso'

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:05.967868


Logo Hivemall 0.3

by myui - March 13, 2015, 17:08:22 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12724 views, 2202 downloads, 3 subscriptions

About: Hivemall is a scalable machine learning library running on Hive/Hadoop.

Changes:
  • Supported Matrix Factorization
  • Added a support for TF-IDF computation
  • Supported AdaGrad/AdaDelta
  • Supported AdaGradRDA classification
  • Added normalization scheme

Logo Torch 3

by bengio - November 13, 2007, 01:38:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8263 views, 2195 downloads, 1 subscription

Rating Whole StarWhole StarWhole Star1/2 StarEmpty Star
(based on 1 vote)

About: Torch is a statistical machine learning library written in C++ at IDIAP,

Changes:

Initial Announcement on mloss.org.


Logo Online Random Forests 0.11

by amirsaffari - October 3, 2009, 17:25:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12169 views, 2184 downloads, 1 subscription

About: This package implements the “Online Random Forests” (ORF) algorithm of Saffari et al., ICCV-OLCV 2009. This algorithm extends the offline Random Forests (RF) to learn from online training data samples. ORF is a multi-class classifier which is able to learn the classifier without 1-vs-all or 1-vs-1 binary decompositions.

Changes:

Initial Announcement on mloss.org.


Showing Items 181-190 of 645 on page 19 of 65: First Previous 14 15 16 17 18 19 20 21 22 23 24 Next Last