About: Incremental (Online) Nonparametric Classifier. You can classify both points (standard) or matrices (multivariate time series). Java and Matlab code already available. Changes:version 2: parameterless system, constant model size, prediction confidence (for active learning). NEW!! C++ version at: https://github.com/ilariagori/ABACOC

About: Jie Gui et al., "How to estimate the regularization parameter for spectral regression discriminant analysis and its kernel version?", IEEE Transactions on Circuits and Systems for Video Technology, vol. 24, no. 2, pp. 211223, 2014 Changes:Initial Announcement on mloss.org. 
About: Jie Gui, Zhenan Sun, Guangqi Hou, Tieniu Tan, "An optimal set of code words and correntropy for rotated least squares regression", International Joint Conference on Biometrics, 2014, pp. 16 Changes:Initial Announcement on mloss.org.

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily. The newest version of xgboost now supports distributed learning on various platforms such as hadoop, mpi and scales to even larger problems Changes:

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 reidentification. For more details, please visit http://www.cbsr.ia.ac.cn/users/scliao/projects/lomo_xqda/. Changes:Initial Announcement on mloss.org.

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, highthroughput, faulttolerant stream processing of data streams. Changes:Initial Announcement on mloss.org.

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.

About: FsAlg is a linear algebra library that supports generic types. Changes:Initial Announcement on mloss.org.

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 crossplatform 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.

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

About: Hivemall is a scalable machine learning library running on Hive/Hadoop. Changes:

About: Libcmaes is a multithreaded C++11 library (with Python bindings) for high performance blackbox stochastic optimization of difficult, possibly nonlinear and nonconvex functions, using the CMAES 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:

About: CN24 is a complete semantic segmentation framework using fully convolutional networks. Changes:Initial Announcement on mloss.org.

About: The DLLearner framework contains several algorithms for supervised concept learning in Description Logics (DLs) and OWL. Changes:See http://dllearner.org/development/changelog/.

About: The autoencoder based data clustering toolkit provides a quick start of clustering based on deep autoencoder nets. This toolkit can cluster data in feature space with a deep nonlinear nets. Changes:Initial Announcement on mloss.org.

About: This is an exact implementation of Histogram of Oriented Gradient as mentioned in the paper by Dalal. Changes:Initial Announcement on mloss.org.

About: The SHOGUN machine learning toolbox's focus is on large scale learning methods with focus on Support Vector Machines (SVM), providing interfaces to python, octave, matlab, r and the command line. Changes:This release features the work of our 8 GSoC 2014 students [student; mentors]:
It also contains several cleanups and bugfixes: Features
Bugfixes
Cleanup and API Changes

About: Distributed optimization: Support Vector Machines and LASSO regression on distributed data Changes:Initial Upload

About: The fertilized forests project has the aim to provide an easy to use, easy to extend, yet fast library for decision forests. It summarizes the research in this field and provides a solid platform to extend it. Offering consistent interfaces to C++, Python and Matlab and being available for all major compilers gives the user high flexibility for using the library. Changes:Initial Announcement on mloss.org.

About: Hubnessaware Machine Learning for Highdimensional Data Changes:
