About: SVM Toolbox fully written in Matlab (even the QP solver). Features : SVM, MultiClassSVM, One-Class, SV Regression, AUC-SVM and Rankboost, 1-norm SVM, Regularization Networks, Kernel Basis Pursuit [...] Changes:Initial Announcement on mloss.org.
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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: SVMlin: Fast Linear SVMs for Supervised and Semi-supervised Learning Changes:Initial Announcement on mloss.org.
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About: BACKGROUND:Over the last decade several prediction methods have been developed for determining the structural and functional properties of individual protein residues using sequence and sequence-derived information. Most of these methods are based on support vector machines as they provide accurate and generalizable prediction models. RESULTS:We present a general purpose protein residue annotation toolkit (svmPRAT) to allow biologists to formulate residue-wise prediction problems. svmPRAT formulates the annotation problem as a classification or regression problem using support vector machines. One of the key features of svmPRAT is its ease of use in incorporating any user-provided information in the form of feature matrices. For every residue svmPRAT captures local information around the reside to create fixed length feature vectors. svmPRAT implements accurate and fast kernel functions, and also introduces a flexible window-based encoding scheme that accurately captures signals and pattern for training eective predictive models. CONCLUSIONS:In this work we evaluate svmPRAT on several classification and regression problems including disorder prediction, residue-wise contact order estimation, DNA-binding site prediction, and local structure alphabet prediction. svmPRAT has also been used for the development of state-of-the-art transmembrane helix prediction method called TOPTMH, and secondary structure prediction method called YASSPP. This toolkit developed provides practitioners an efficient and easy-to-use tool for a wide variety of annotation problems. Availability: http://www.cs.gmu.edu/~mlbio/svmprat/ Changes:Initial Announcement on mloss.org.
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About: svm-struct-matlab is a MATLAB wrapper of T. Joachims' SVM^struct solver for structured output support vector machines. Changes:Adds support for Xcode 4.0 and Mac OS X 10.7 and greater.
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About: SVQP1 and SVQP2 are QP solvers for training SVM. Changes:Initial Announcement on mloss.org.
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About: Tapkee is an efficient and flexible C++ template library for dimensionality reduction. Changes:Initial Announcement on mloss.org.
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About: TBEEF, a doubly ensemble framework for recommendation and prediction problems. Changes:Included the final technical report.
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About: Tekkotsu is a high-level framework for robot programming that provides primitives for perception, manipulation, navigation, and control. It supports a variety of robot platforms. Changes:Initial Announcement on mloss.org.
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About: Test submission. Is MLOSS working? Changes:Initial Announcement on mloss.org.
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About: Regularization paTH for LASSO problem (thalasso) thalasso solves problems of the following form: minimize 1/2||X*beta-y||^2 + lambda*sum|beta_i|, where X and y are problem data and beta and lambda are variables. Changes:Initial Announcement on mloss.org.
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About: The package computes the optimal parameters for the Choquet kernel Changes:Initial Announcement on mloss.org.
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About: The glm-ie toolbox contains scalable estimation routines for GLMs (generalised linear models) and SLMs (sparse linear models) as well as an implementation of a scalable convex variational Bayesian inference relaxation. We designed the glm-ie package to be simple, generic and easily expansible. Most of the code is written in Matlab including some MEX files. The code is fully compatible to both Matlab 7.x and GNU Octave 3.2.x. Probabilistic classification, sparse linear modelling and logistic regression are covered in a common algorithmical framework allowing for both MAP estimation and approximate Bayesian inference. Changes:added factorial mean field inference as a third algorithm complementing expectation propagation and variational Bayes generalised non-Gaussian potentials so that affine instead of linear functions of the latent variables can be used
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About: GIDOC (Gimp-based Interactive transcription of old text DOCuments) is a computer-assisted transcription prototype for handwritten text in old documents. It is a first attempt to provide integrated support for interactive-predictive page layout analysis, text line detection and handwritten text transcription. GIDOC is built on top of the well-known GNU Image Manipulation Program (GIMP), and uses standard techniques and tools for handwritten text preprocessing and feature extraction, HMM-based image modelling, and language modelling. Changes:Updated version for mloss 2010
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About: An implementation of the infinite hidden Markov model. Changes:Since 0.4: Removed dependency from lightspeed (now using statistics toolbox). Updated to newer matlab versions.
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About: STK++: A Statistical Toolkit Framework in C++ Changes:Inegrating openmp to the current release. Many enhancement in the clustering project. bug fix
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About: A Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Dynamically generates CPU and GPU modules for good performance. Deep Learning Tutorials illustrate deep learning with Theano. Changes:Theano 1.0.2 (23rd of May, 2018)This is a maintenance release of Theano, version We recommend that everybody update to this version. Highlights (since 1.0.1):
A total of 6 people contributed to this release since
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About: This is demo program on global thresholding for image of bright small objects, such as aircrafts in airports. the program include four method, otsu,2D-Tsallis,PSSIM, Smoothnees Method. Changes:Initial Announcement on mloss.org.
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