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About: This MATLAB package provides the LOMO feature extraction and the XQDA metric learning algorithms proposed in our CVPR 2015 paper. It is fast, and effective for person re-identification. For more details, please visit http://www.cbsr.ia.ac.cn/users/scliao/projects/lomo_xqda/. Changes:Initial Announcement on mloss.org.
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About: Nilearn is a Python module for fast and easy statistical learning on NeuroImaging data. It leverages the scikit-learn Python toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis. Changes:Initial Announcement on mloss.org.
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About: FAST is an implementation of Hidden Markov Models with Features. It allows features to modify both emissions and transition probabilities. Changes:Initial Announcement on mloss.org.
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About: MIPS is a software library for state-of-the-art graph mining algorithms. The library is platform independent, written in C++(03), and aims at implementing generic and efficient graph mining algorithms. Changes:description update
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About: streamDM is a new open source data mining and machine learning library, designed on top of Spark Streaming, an extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of data streams. Changes:Initial Announcement on mloss.org.
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About: Bayesian Logic (BLOG) is a probabilistic modeling language. It is designed for representing relations and uncertainties among real world objects. Changes:Initial Announcement on mloss.org.
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About: FsAlg is a linear algebra library that supports generic types. Changes:Initial Announcement on mloss.org.
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About: This Matlab package implements a method for learning a choquistic regression model (represented by a corresponding Moebius transform of the underlying fuzzy measure), using the maximum likelihood approach proposed in [2], eqquiped by sigmoid normalization, see [1]. Changes:Initial Announcement on mloss.org.
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About: Jmlp is a java platform for both of the machine learning experiments and application. I have tested it on the window platform. But it should be applicable in the linux platform due to the cross-platform of Java language. It contains the classical classification algorithm (Discrete AdaBoost.MH, Real AdaBoost.MH, SVM, KNN, MCE,MLP,NB) and feature reduction(KPCA,PCA,Whiten) etc. Changes:Initial Announcement on mloss.org.
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About: A Theano framework for building and training neural networks Changes:Initial Announcement on mloss.org.
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About: A Tool for Embedding Strings in Vector Spaces Changes:Support for explicit selection of granularity added. Several minor bug fixes. We have reached 1.0
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About: A streaming inference and query engine for the Cross-Categorization model of tabular data. Changes:Initial Announcement on mloss.org.
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About: A toolkit for hyperparameter optimization for machine learning algorithms. Changes:Initial Announcement on mloss.org.
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About: Hivemall is a scalable machine learning library running on Hive/Hadoop. Changes:
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About: Libcmaes is a multithreaded C++11 library (with Python bindings) for high performance blackbox stochastic optimization of difficult, possibly non-linear and non-convex functions, using the CMA-ES algorithm for Covariance Matrix Adaptation Evolution Strategy. Libcmaes is useful to minimize / maximize any function, without information regarding gradient or derivability. Changes:This is a major release, with several novelties, improvements and fixes, among which:
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About: Mulan is an open-source Java library for learning from multi-label datasets. Multi-label datasets consist of training examples of a target function that has multiple binary target variables. This means that each item of a multi-label dataset can be a member of multiple categories or annotated by many labels (classes). This is actually the nature of many real world problems such as semantic annotation of images and video, web page categorization, direct marketing, functional genomics and music categorization into genres and emotions. Changes:Learners
Measures/Evaluation
Bug fixes
API changes
Miscalleneous
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About: CN24 is a complete semantic segmentation framework using fully convolutional networks. Changes:Initial Announcement on mloss.org.
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About: MALSS is a python module to facilitate machine learning tasks. Changes:Initial Announcement on mloss.org.
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About: The DL-Learner framework contains several algorithms for supervised concept learning in Description Logics (DLs) and OWL. Changes:See http://dl-learner.org/development/changelog/.
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About: The auto-encoder based data clustering toolkit provides a quick start of clustering based on deep auto-encoder nets. This toolkit can cluster data in feature space with a deep nonlinear nets. Changes:Initial Announcement on mloss.org.
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