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About: A Graphical Tool for Designing and Training Deep Neural Networks Changes:
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About: RLS2 is an instance of multiple kernel learning algorithm to simultaneously learn a regularized predictor and the kernel function. RLS2LIN is a version of RLS2 specialized to linear kernels on each feature. The package contains a set of scripts that implements RLS2 and RLS2LIN, together with a Graphic User Interface to load data, perform training, validation, and plot results. Changes:
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About: Regression Trees with Random Effects for Longitudinal (Panel) Data Changes:Fetched by r-cran-robot on 2013-04-01 00:00:08.040424
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About: Very fast implementation of the chi-squared distance between histograms (or vectors with non-negative entries). Changes:Removed bug in symmetric chi-square distance and updated python wrapper to python 2.5 compatiblity. |
About: kernlab provides kernel-based Machine Learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods kernlab [...] Changes:minor fixes in kcca and ksvm functions
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About: L1 constrained estimation aka `lasso' Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.967868
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About: Investigation of dependencies between multiple data sources allows the discovery of regularities and interactions that are not seen in individual data sets. The demand for such methods is increasing with the availability and size of co-occurring observations in computational biology, open data initiatives, and in other domains. We provide practical, open access implementations of general-purpose algorithms that help to realize the full potential of these information sources. Changes:Three independent modules (drCCA, pint, MultiWayCCA) have been added.
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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.
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About: Accurate splice site predictor for a variety of genomes. Changes:Asp now supports three formats: -g fname for gff format -s fname for spf format -b dir for a binary format compatible with mGene. And a new switch -t which switches on a sigmoid-based transformation of the svm scores to get scores between 0 and 1.
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About: Generalized Boosted Regression Models Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.019963
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About: OpenKernel is a library for creating, combining, learning and using kernels for machine learning applications. Changes:Initial Announcement on mloss.org.
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About: This package contains functions to estimate linear and nonlinear regression methods with Penalized Partial Least Squares. Changes:
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About: Variable selection using random forests Changes:Fetched by r-cran-robot on 2012-02-01 00:00:12.245883
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About: R genetic programming framework Changes:Fetched by r-cran-robot on 2013-04-01 00:00:08.163887
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About: SMPyBandits: an Open-Source Research Framework for Single and Multi-Players Multi-Arms Bandits (MAB) Algorithms in Python Changes:Initial Announcement on mloss.org.
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About: This local and parallel computation toolbox is the Octave and Matlab implementation of several localized Gaussian process regression methods: the domain decomposition method (Park et al., 2011, DDM), partial independent conditional (Snelson and Ghahramani, 2007, PIC), localized probabilistic regression (Urtasun and Darrell, 2008, LPR), and bagging for Gaussian process regression (Chen and Ren, 2009, BGP). Most of the localized regression methods can be applied for general machine learning problems although DDM is only applicable for spatial datasets. In addition, the GPLP provides two parallel computation versions of the domain decomposition method. The easiness of being parallelized is one of the advantages of the localized regression, and the two parallel implementations will provide a good guidance about how to materialize this advantage as software. Changes:Initial Announcement on mloss.org.
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About: hapFabia is an R package for identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data. It detects 100 times smaller segments than previous methods. Changes:o citation update o plot function improved
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About: The open source Error-Correcting Output Codes (ECOC) library contains both state-of-the-art coding and decoding designs, as well as the option to include your own coding, decoding, and base classifier. Changes:Initial Announcement on mloss.org.
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About: Reference implementation of the LASVM online and active SVM algorithms as described in the JMLR paper. The interesting bit is a small C library that implements the LASVM process and reprocess [...] Changes:Minor bug fix
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About: This software implements the DeltaLDA model, which is a modification of the Latent Dirichlet Allocation (LDA) model. DeltaLDA can use multiple topic mixing weight priors to jointly model multiple [...] Changes:-fixed some npy_intp[] memory leaks -fixed phi normalization bug
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