RSS Feed - Blog
About: Matlab implementation of variational gaussian approximate inference for Bayesian Generalized Linear Models. Changes:Code restructure and bug fix.
|
About: This is the source code of the mloss.org website. Changes:Now works with newer django versions and fixes several warnings and minor bugs underneath. The only user visible change is probably that the subscription and bookmark buttons work again.
|
About: A chatterbot that learns natural languages learning from imitation. Changes:Alpha 1 - Codename: Wendell Borton ("Bllluuhhhhh...!!") Short term memory greatly improved.
|
About: Tools for functional network analysis. Changes:Initial Announcement on mloss.org.
|
About: A work in progress Changes:Initial Announcement on mloss.org.
|
|
About: Variable selection using random forests Changes:Fetched by r-cran-robot on 2012-02-01 00:00:12.245883
|
About: KeplerWeka represents the integration of all the functionality of the WEKA Machine Learning Workbench into the open-source scientific workflow Kepler. Among them are classification, [...] Changes:
|
About: Ordinal classification tree functions Changes:Initial Announcement on mloss.org by r-cran-robot
|
About: The SUMO Toolbox is a Matlab toolbox that automatically builds accurate surrogate models (also known as metamodels or response surface models) of a given data source (e.g., simulation code, data set, script, ...) within the accuracy and time constraints set by the user. The toolbox minimizes the number of data points (which it selects automatically) since they are usually expensive. Changes:Incremental update, fixing some cosmetic issues, coincides with JMLR publication.
|
About: The gmm toolbox contains code for density estimation using mixtures of Gaussians: Starting from simple kernel density estimation with spherical and diagonal Gaussian kernels over manifold Parzen window until mixtures of penalised full Gaussians with only a few components. The toolbox covers many Gaussian mixture model parametrisations from the recent literature. Most prominently, the package contains code to use the Gaussian Process Latent Variable Model for density estimation. Most of the code is written in Matlab 7.x including some MEX files. Changes:Initial Announcement on mloss.org
|
About: A stochastic variant of the mirror descent algorithm employing Langford and Zhang's truncated gradient idea to minimize L1 regularized loss minimization problems for classification and regression. Changes:Fixed major bug in implementation. The components of the iterate where the current example vector is zero were not being updated correctly. Thanks to Jonathan Chang for pointing out the error to us.
|
About: Feature Selection SVM using penalty functions Changes:Fetched by r-cran-robot on 2013-04-01 00:00:07.509844
|
About: An implementation of the infinite hidden Markov model. Changes:Since 0.4: Removed dependency from lightspeed (now using statistics toolbox). Updated to newer matlab versions.
|
About: Toolbox for circular statistics with Matlab (The Mathworks). Changes:Some bugfixes.
|
About: Random Survival Forests Changes:Fetched by r-cran-robot on 2013-03-01 00:00:08.083405
|
About: OpenKernel is a library for creating, combining, learning and using kernels for machine learning applications. Changes:Initial Announcement on mloss.org.
|
About: yaplf (Yet Another Python Learning Framework) is an extensible machine learning framework written in python Changes:Initial Announcement on mloss.org.
|
About: This software package implements a series of statistical mixture models for bilingual text classificacion trained by the EM algorihtm. Changes:Initial Announcement on mloss.org.
|
|
About: Orthonormal wavelet transform for D dimensional tensors in L levels. Generic quadrature mirror filters and tensor sizes. Runtime is O(n), plain C, MEX-wrapper and demo provided. Changes:Initial Announcement on mloss.org. |
