About: This program implements a novel robust sparse representation method, called the twostage sparse representation (TSR), for robust recognition on a largescale database. Based on the divide and conquer strategy, TSR divides the procedure of robust recognition into outlier detection stage and recognition stage. The extensive numerical experiments on several public databases demonstrate that the proposed TSR approach generally obtains better classification accuracy than the stateoftheart Sparse Representation Classification (SRC). At the same time, by using the TSR, a significant reduction of computational cost is reached by over fifty times in comparison with the SRC, which enables the TSR to be deployed more suitably for largescale dataset. Changes:Initial Announcement on mloss.org.

About: This is a implementation of the classic P3P(Perspective 3Points) algorithm problem solution in the Ransac paper "M. A. Fischler, R. C. Bolles. Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Comm. of the ACM, Vol 24, pp 381395, 1981.". The algorithm gives the four probable solutions of the P3P problem in about 0.1ms, and can be used as input of the consequent RANSAC step. The codes needs the numerics library VNL which is a part of the widely used computer vision library VXL. One can download & install it from http://vxl.sourceforge.net/. Changes:Initial Announcement on mloss.org.

About: It's a C++ program for symmetric matrix diagonalization, inversion and principal component anlaysis(PCA). The matrix diagonalization function can also be applied to the computation of singular value decomposition (SVD), Fisher linear discriminant analysis (FLDA) and kernel PCA (KPCA) if forming the symmetric matrix appropriately. Changes:Initial Announcement on mloss.org.

About: This program is a C++ implementation of Linear Discriminant Function Classifier. Discriminant functions such as perceptron criterion, cross entropy (CE) criterion, and least mean square (LMS) criterion (all for multiclass classification problems) are supported in it. The program uses a sparsedata structure to represent the feature vector to seek higher computational speed. Some other techniques such as online updating, weights averaging, gaussian prior regularization are also supported. Changes:Initial Announcement on mloss.org.

About: This program is a C++ implementation of Naive Bayes Classifier, which is a wellknown generative classification algorithm for the application such as text classification. The Naive Bayes algorithm requires the probabilistic distribution to be discrete. The program uses the multinomial event model for representation, the maximum likelihood estimate with a Laplace smoothing technique for learning parameters. A sparsedata structure is defined to represent the feature vector in the program to seek higher computational speed. Changes:Initial Announcement on mloss.org.

About: A simple and clear OpenCV based extended Kalman filter(EKF) abstract class implementation,absolutely following standard EKF equations. Special thanks to the open source project of KFilter1.3. It is easy to inherit it to implement a variable state and measurement EKF for computer vision and INS usages. Changes:Initial Announcement on mloss.org.

About: Supervised Latent Semantic Indexing(SLSI) is an supervised feature transformation method. The algorithms in this package are based on the iterative algorithm of Latent Semantic Indexing. Changes:Initial Announcement on mloss.org.

About: This program is used to extract SIFT points from an image. Changes:Initial Announcement on mloss.org.

About: This program is used to extract HOG(histograms of oriented gradients) features from images. The integral histogram is used for fast histogram extraction. Both APIs and binary utility are provided. Changes:Initial Announcement on mloss.org.

About: This program is used to find point matches between two images. The procedure can be divided into two parts: 1) use SIFT matching algorithm to find sparse point matches between two images. 2) use "quasidense propagation" algorithm to get "quasidense" point matches. Changes:Initial Announcement on mloss.org.

About: Hofmann, T. 1999. Probabilistic latent semantic indexing. In Proceedings of the 22nd ACMSIGIR International Conference on Research and Development in Information Retrieval (Berkeley,Calif.), ACM, New York, 50–57. Changes:Initial Announcement on mloss.org.

About: MeanShift (MS) is a powerful nonparametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets. For the purpose of algorithm speedup, an agglomerative MS clustering method called AggloMS was developed, along with its modeseeking ability and convergence property analysis. The method is built upon an iterative query set compression mechanism which is motivated by the quadratic bounding optimization nature of MS. The whole framework can be efficiently implemented in linear running time complexity. Changes:Initial Announcement on mloss.org.

About: The toolbox is to calculate normalized information measures from a given m by (m+1) confusion matrix for objective evaluations of an abstaining classifier. It includes total 24 normalized information measures based on three groups of definitions, that is, mutual information, information divergence, and cross entropy. Changes:Initial Announcement on mloss.org.

About: Scilab Pattern Recognition Toolbox is a toolbox developed for Scilab software, and is used in pattern recognition, machine learning and the related field. It is developed for the purpose of education and research. Changes:Initial Announcement on mloss.org.

About: Learns gradient boosted regression tree ensembles in parallel on shared memory or cluster systems Changes:Initial Announcement on mloss.org.

About: Pyriel is a Python system for learning classification rules from data. Unlike other rule learning systems, it is designed to learn rule lists that maximize the area under the ROC curve (AUC) instead of accuracy. Pyriel is mostly an experimental research tool, but it's robust and fast enough to be used for lightweight industrial data mining. Changes:1.5 Changed CF (confidence factor) to do LaPlace smoothing of estimates. New flag "scoreforclass C" causes scores to be computed relative to a given (positive) class. For twoclass problems. Fixed bug in example sampling code (sample n) Fixed bug keeping oldstyle example formats (terminated by dot) from working. More code restructuring.

About: jblas is a fast linear algebra library for Java. jblas is based on BLAS and LAPACK, the defacto industry standard for matrix computations, and uses stateoftheart implementations like ATLAS for all its computational routines, making jBLAS very fast. Changes:Changes from 1.0:

About: Toolbox for circular statistics with Matlab (The Mathworks). Changes:Some bugfixes.

About: This toolbox provides functions for maximizing and minimizing submodular set functions, with applications to Bayesian experimental design, inference in Markov Random Fields, clustering and others. Changes:
