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About: Shrunken Centroids Regularized Discriminant Analysis Changes:Fetched by rcranrobot on 20130401 00:00:07.868841

About: In this paper, we propose an improved principal component analysis based on maximum entropy (MaxEnt) preservation, called MaxEntPCA, which is derived from a Parzen window estimation of Renyi’s quadratic entropy. Instead of minimizing the reconstruction error either based on L2norm or L1norm, the MaxEntPCA attempts to preserve as much as possible the uncertainty information of the data measured by entropy. The optimal solution of MaxEntPCA consists of the eigenvectors of a Laplacian probability matrix corresponding to the MaxEnt distribution. MaxEntPCA (1) is rotation invariant, (2) is free from any distribution assumption, and (3) is robust to outliers. Extensive experiments on realworld datasets demonstrate the effectiveness of the proposed linear method as compared to other related robust PCA methods. Changes:Initial Announcement on mloss.org.

About: Scalable tensor factorization Changes:

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 Matlab benchmarking toolbox for online and adaptive regression with kernels. Changes:

About: A Matlab implementation of Uncorrelated Multilinear Discriminant Analysis (UMLDA) for dimensionality reduction of tensor data via tensortovector projection Changes:Initial Announcement on mloss.org.

About: OpenPRNBEM is an 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. OpenPRNBEM uses the multinomial event model for representation. The maximum likelihood estimate is used for supervised learning, and the expectationmaximization estimate is used for semisupervised and unsupervised learning. 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. Changes:New features:  R support that is now on CRAN

About: Cluster quality Evaluation software. Implements cluster quality metrics based on ground truths such as Purity, Entropy, Negentropy, F1 and NMI. It includes a novel approach to correct for pathological or ineffective clusterings called 'Divergence from a Random Baseline'. Changes:Initial Announcement on mloss.org.

About: PyStruct is a framework for learning structured prediction in Python. It has a modular interface, similar to the wellknown SVMstruct. Apart from learning algorithms it also contains model formulations for popular CRFs and interfaces to many inference algorithm implementation. Changes:Initial Announcement on mloss.org.
