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Logo WebEnsemble 1.0

by jungc005 - May 8, 2012, 22:24:44 CET [ BibTeX Download ] 2051 views, 778 downloads, 1 subscription

About: Use the power of crowdsourcing to create ensembles.

Changes:

Initial Announcement on mloss.org.


Logo Weight HMM 1.0

by SongTao - May 27, 2014, 15:29:20 CET [ BibTeX Download ] 1182 views, 480 downloads, 1 subscription

About: Discovering short linear protein motif based on selective training of profile hidden Markov models

Changes:

Initial Announcement on mloss.org.


Logo WEKA 3.7.13

by mhall - September 11, 2015, 04:55:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 53706 views, 7985 downloads, 4 subscriptions

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About: The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modelling, together with graphical user interfaces for easy access to this [...]

Changes:

In core weka:

  • Numerically stable implementation of variance calculation in core Weka classes - thanks to Benjamin Weber
  • Unified expression parsing framework (with compiled expressions) is now employed by filters and tools that use mathematical/logical expressions - thanks to Benjamin Weber
  • Developers can now specify GUI and command-line options for their Weka schemes via a new unified annotation-based mechanism
  • ClassConditionalProbabilities filter - replaces the value of a nominal attribute in a given instance with its probability given each of the possible class values
  • GUI package manager's available list now shows both packages that are not currently installed, and those installed packages for which there is a more recent version available that is compatible with the base version of Weka being used
  • ReplaceWithMissingValue filter - allows values to be randomly (with a user-specified probability) replaced with missing values. Useful for experimenting with methods for imputing missing values
  • WrapperSubsetEval can now use plugin evaluation metrics

In packages:

  • alternatingModelTrees package - alternating trees for regression
  • timeSeriesFilters package, contributed by Benjamin Weber
  • distributedWekaSpark package - wrapper for distributed Weka on Spark
  • wekaPython package - execution of CPython scripts and wrapper classifier/clusterer for Scikit Learn schemes
  • MLRClassifier in RPlugin now provides access to almost all classification and regression learners in MLR 2.4

Logo WolfeSVM 0.0

by utmath - November 19, 2014, 10:46:11 CET [ Project Homepage BibTeX Download ] 1300 views, 375 downloads, 2 subscriptions

About: This is a library for solving nu-SVM by using Wolfe's minimum norm point algorithm. You can solve binary classification problem.

Changes:

Initial Announcement on mloss.org.


Logo WordNet Similarity 2.05

by tpederse - August 12, 2008, 16:42:50 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6649 views, 1657 downloads, 2 subscriptions

About: This is a Perl module that implements a variety of semantic similarity and relatedness measures based on information found in the lexical database WordNet. In particular, it supports the measures of [...]

Changes:

Initial Announcement on mloss.org.


Logo XGBoost v0.4.0

by crowwork - May 12, 2015, 08:57:16 CET [ Project Homepage BibTeX Download ] 11144 views, 2143 downloads, 3 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:
  • Distributed version of xgboost that runs on YARN, scales to billions of examples

  • Direct save/load data and model from/to S3 and HDFS

  • Feature importance visualization in R module, by Michael Benesty

  • Predict leaf index

  • Poisson regression for counts data

  • Early stopping option in training

  • Native save load support in R and python

  • xgboost models now can be saved using save/load in R

  • xgboost python model is now pickable

  • sklearn wrapper is supported in python module

  • Experimental External memory version


About: Stochastic neighbor embedding originally aims at the reconstruction of given distance relations in a low-dimensional Euclidean space. This can be regarded as general approach to multi-dimensional scaling, but the reconstruction is based on the definition of input (and output) neighborhood probability alone. The present implementation also allows for handling dissimilarity or score-induced neighborhood topologies and makes use of quasi 2nd order gradient-based (l-)BFGS optimization.

Changes:
  • gradient in xsne_fun.m fixed! (constant factor m was missing)

  • symmetry option re-introduced allowing for enabling symmetric and asymmetric versions of SNE and t-SNE


Logo yaplf 0.7

by malchiod - April 22, 2010, 11:34:07 CET [ Project Homepage BibTeX Download ] 4363 views, 1097 downloads, 1 subscription

About: yaplf (Yet Another Python Learning Framework) is an extensible machine learning framework written in python

Changes:

Initial Announcement on mloss.org.


Logo YCML 0.2.2

by yconst - August 24, 2015, 20:28:45 CET [ Project Homepage BibTeX Download ] 1015 views, 208 downloads, 3 subscriptions

About: A Machine Learning framework for Objective-C and Swift (OS X / iOS)

Changes:

Initial Announcement on mloss.org.


Showing Items 601-609 of 609 on page 61 of 61: First Previous 56 57 58 59 60 61