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Showing Items 91-100 of 623 on page 10 of 63: First Previous 5 6 7 8 9 10 11 12 13 14 15 Next Last

Logo r-cran-randomForest 4.6-7

by r-cran-robot - October 16, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 16078 views, 3266 downloads, 1 subscription

About: Breiman and Cutler's random forests for classification and regression

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:07.638240


Logo JProGraM 13.2

by ninofreno - February 13, 2013, 20:29:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15805 views, 3102 downloads, 1 subscription

About: JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random graphs/fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.

Changes:

JProGraM 13.2 -- CHANGE LOG

Release date: February 13, 2012

New features: -- Support for Fiedler random graphs/random field models for large-scale networks (ninofreno.graph.fiedler package); -- Various bugfixes and enhancements (especially in the ninofreno.graph and ninofreno.math package).


Logo Pyriel 1.5

by tfawcett - October 27, 2010, 09:12:53 CET [ BibTeX BibTeX for corresponding Paper Download ] 15792 views, 3685 downloads, 1 subscription

About: Pyriel is a Python system for learning classification rules from data. Unlike other rule learning systems, it is designed to learn rule lists that maximize the area under the ROC curve (AUC) instead of accuracy. Pyriel is mostly an experimental research tool, but it's robust and fast enough to be used for lightweight industrial data mining.

Changes:

1.5 Changed CF (confidence factor) to do LaPlace smoothing of estimates. New flag "--score-for-class C" causes scores to be computed relative to a given (positive) class. For two-class problems. Fixed bug in example sampling code (--sample n) Fixed bug keeping old-style example formats (terminated by dot) from working. More code restructuring.


Logo r-cran-tgp 2.4-3

by r-cran-robot - December 18, 2011, 00:00:00 CET [ Project Homepage BibTeX Download ] 15731 views, 3272 downloads, 1 subscription

About: Bayesian treed Gaussian process models

Changes:

Fetched by r-cran-robot on 2012-02-01 00:00:11.834310


Logo LIBOL 0.3.0

by stevenhoi - December 12, 2013, 15:26:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15702 views, 5655 downloads, 2 subscriptions

About: LIBOL is an open-source library with a family of state-of-the-art online learning algorithms for machine learning and big data analytics research. The current version supports 16 online algorithms for binary classification and 13 online algorithms for multiclass classification.

Changes:

In contrast to our last version (V0.2.3), the new version (V0.3.0) has made some important changes as follows:

• Add a template and guide for adding new algorithms;

• Improve parameter settings and make documentation clear;

• Improve documentation on data formats and key functions;

• Amend the "OGD" function to use different loss types;

• Fixed some name inconsistency and other minor bugs.


Logo JMLR Model Monitor 1.0

by traeder - August 17, 2009, 11:05:06 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15638 views, 2168 downloads, 0 comments, 1 subscription

About: Model Monitor is a Java toolkit for the systematic evaluation of classifiers under changes in distribution. It provides methods for detecting distribution shifts in data, comparing the performance [...]

Changes:

Improved AUROC calculation. Several minor bug fixes.


Logo libAGF 0.9.8

by Petey - December 6, 2014, 02:35:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 15287 views, 2948 downloads, 2 subscriptions

About: C++ software for statistical classification, probability estimation and interpolation/non-linear regression using variable bandwidth kernel estimation.

Changes:

New in Version 0.9.8:

  • bug fixes: svm file conversion works properly and is more general

  • non-hierarchical multi-borders has 3 options for solving for the conditional probabilities: matrix inversion, voting, and matrix inversion over-ridden by voting, with re-normalization

  • multi-borders now works with external binary classifiers

  • random numbers resolve a tie when selecting classes based on probabilities

  • pair of routines, sort_discrete_vectors and search_discrete_vectors, for classification based on n-d binning (still experimental)

  • command options have been changed with many new additions, see QUICKSTART file or run the relevant commands for details


Logo JMLR JNCC2 1.11

by gcorani - January 1, 2009, 03:22:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14920 views, 1861 downloads, 0 comments, 1 subscription

About: JNCC2 is the open-source implementation of the Naive Credal Classifier2 (NCC2), i.e., an extension of Naive Bayes towards imprecise probabilities, designed to deliver robust classifications even on [...]

Changes:

Initial Announcement on mloss.org.


Logo BayesPy 0.4.1

by jluttine - November 2, 2015, 13:40:09 CET [ Project Homepage BibTeX Download ] 14882 views, 3349 downloads, 3 subscriptions

About: Variational Bayesian inference tools for Python

Changes:
  • Define extra dependencies needed to build the documentation

Logo FABIA 2.8.0

by hochreit - October 18, 2013, 10:14:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 14306 views, 2947 downloads, 1 subscription

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About: FABIA is a biclustering algorithm that clusters rows and columns of a matrix simultaneously. Consequently, members of a row cluster are similar to each other on a subset of columns and, analogously, members of a column cluster are similar to each other on a subset of rows. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. Applications include detection of transcriptional modules in gene expression data and identification of haplotypes/>identity by descent< consisting of rare variants obtained by next generation sequencing.

Changes:

CHANGES IN VERSION 2.8.0

NEW FEATURES

o rescaling of lapla
o extractPlot does not plot sorted matrices

CHANGES IN VERSION 2.4.0

o spfabia bugfixes

CHANGES IN VERSION 2.3.1

NEW FEATURES

o Getters and setters for class Factorization

2.0.0:

  • spfabia: fabia for a sparse data matrix (in sparse matrix format) and sparse vector/matrix computations in the code to speed up computations. spfabia applications: (a) detecting >identity by descent< in next generation sequencing data with rare variants, (b) detecting >shared haplotypes< in disease studies based on next generation sequencing data with rare variants;
  • fabia for non-negative factorization (parameter: non_negative);
  • changed to C and removed dependencies to Rcpp;
  • improved update for lambda (alpha should be smaller, e.g. 0.03);
  • introduced maximal number of row elements (lL);
  • introduced cycle bL when upper bounds nL or lL are effective;
  • reduced computational complexity;
  • bug fixes: (a) update formula for lambda: tighter approximation, (b) corrected inverse of the conditional covariance matrix of z;

1.4.0:

  • New option nL: maximal number of biclusters per row element;
  • Sort biclusters according to information content;
  • Improved and extended preprocessing;
  • Update to R2.13

Showing Items 91-100 of 623 on page 10 of 63: First Previous 5 6 7 8 9 10 11 12 13 14 15 Next Last