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About: The aim is to embed a given data relationship matrix into a low-dimensional Euclidean space such that the point distances / distance ranks correlate best with the original input relationships. Input relationships may be given as (sparse) (asymmetric) distance, dissimilarity, or (negative!) score matrices. Input-output relations are modeled as low-conditioned. (Weighted) Pearson and soft Spearman rank correlation, and unweighted soft Kendall correlation are supported correlation measures for input/output object neighborhood relationships. Changes:
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About: A Matlab implementation of Sparse PCA using the inverse power method for nonlinear eigenproblems. Changes:
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About: Bayesian Additive Regression Trees Changes:Fetched by r-cran-robot on 2018-09-01 00:00:04.021726
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About: MOSIS is a modularized framework for signal processing, stream analysis, machine learning and stream mining applications. Changes:
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About: Matlab code for learning probabilistic SVM in the presence of uncertain labels. Changes:Added missing dataset function (thanks to Hao Wu)
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About: Data-efficient policy search framework using probabilistic Gaussian process models Changes:Initial Announcement on mloss.org.
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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.
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About: Debellor is a scalable and extensible platform which provides common architecture for data mining and machine learning algorithms of various types. Changes:
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About: This software is aimed at performing supervised/unsupervised learning on graph data, where each graph is represented as binary indicators of subgraph features. Changes:Initial Announcement on mloss.org.
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About: Learns gradient boosted regression tree ensembles in parallel on shared memory or cluster systems Changes:Initial Announcement on mloss.org.
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About: SeqAn is an open source C++ library of efficient algorithms and data structures for the analysis of sequences with the focus on biological data. Changes:
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About: A Matlab implementation of Multilinear PCA (MPCA) and MPCA+LDA for dimensionality reduction of tensor data with sample code on gait recognition Changes:
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About: The K-tree is a scalable approach to clustering inspired by the B+-tree and k-means algorithms. Changes:Release of K-tree implementation in Python. This is targeted at a research and rapid prototyping audience.
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About: HDDM is a python toolbox for hierarchical Bayesian parameter estimation of the Drift Diffusion Model (via PyMC). Drift Diffusion Models are used widely in psychology and cognitive neuroscience to study decision making. Changes:
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About: pySPACE is the abbreviation for "Signal Processing and Classification Environment in Python using YAML and supporting parallelization". It is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface. Changes:improved testing, improved documentation, windows compatibility, more algorithms
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About: The Rchemcpp package implements the marginalized graph kernel and extensions, Tanimoto kernels, graph kernels, pharmacophore and 3D kernels suggested for measuring the similarity of molecules. Changes:Moved from CRAN to Bioconductor. Improved handling of molecules, visualization and examples.
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About: Multicore/distributed large scale machine learning framework. Changes:Update version.
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About: Implementation of the multi-assignment clustering method for Boolean vectors. Changes:new bib added
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About: A native Python, scikit-compatible, implementation of a variety of multi-label classification algorithms. Changes:
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About: Matlab Multiple Kernel Learning toolbox. Features : MKL for SVM Classification, Regression and MultiClass. It needs SVM-KM Toolbox Changes:Initial Announcement on mloss.org.
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