Search Results for "support vector machine classifier" - Page 3

The package is used to classify protein coding and long non-coding RNA (lncRNA) transcripts using support vector machine (SVM).

Credit Risk Evaluation Using Support Vector Machine

Applying the LIBSVM, a package of support vector machine, SAMSVM was developed to correctly detect and filter the misaligned reads of SAM format. Such filtration can reduce false positives in alignment and the following variant analysis.

PiSvM is a parallel Support Vector Machine (SVM) implementation. It supports C-SVC, nu-SVC, epsilon-SVR and nu-SVR and has a command-line interface similar to the popular LibSVM package.

We present BudgetedSVM, a C++ toolbox containing highly optimized implementations of three recently proposed algorithms for scalable training of Support Vector Machine (SVM) approximators: Adaptive Multi-hyperplane Machines (AMM), Budgeted Stochastic Gradient Descent (BSGD), and Low-rank Linearization SVM (LLSVM). BudgetedSVM trains models with accuracy comparable to LibSVM in time comparable to LibLinear, as it allows solving highly non-linear classification problems with millions of high-dimensional examples within minutes on a regular personal computer. ...

This program reads a fasta file specified by -i option, then, converts it to SVM Light format, further runs the classification module of SVM Light and then evaluate the predictions. The support vector machine models were based on 310 antimicrobial peptide sequences extracted from antimicrobial peptides database and 310 non-antimicrobial peptide sequences extracted from protein data bank. The system's accuracy is 90% by using the polynomial model (default).

...In screening stage, Co-Information Filter (CIF) is employed to visualize and rank contributions of individual SNPs to the phenotype. The number of top ranking SNPs retained to next stage is specified by users directly or a support vector machine classifier automatically. In testing stage, co-information and co-information based permutation test are conducted sequentially to exhaustively search epistasis within the retained SNPs and the final results are then ranked by their p-values. For characterizing broader epistasis landscape, networks are built freely in visualizing stage by linking pairs of the retained SNPs if their co-information values with respect to the phenotype are

The Stanford Machine Learning Course Exercises repository contains programming assignments from the well-known Stanford Machine Learning online course. It includes implementations of a variety of fundamental algorithms using Python and MATLAB/Octave. The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems.

HSSVM(Hyper-Sphere Support Vector Machines) is a software for solving multi-classification problem, implemented by Java.

SVM# is a svm(support vector machine) classification implemented in C#. The project contains both train and predict modules.

GPU library for simple development of OpenGL-based GPGPU applications, offscreen rendering and shading techniques.

HIVM, An Application for Prediction of HIV Drug Resistance using Support Vector Machine Algorithms

mex-svm is a set of patches against SVM-Light to compile into "mex" libraries and enable fast Support Vector Machine evaluation from within MATLAB.

ARGMAX is an open source implementation of structured models; conditional random fields and structural support vector machine.

The simpleSVM project contains Machine Learning codes for algorithms based on the SimpleSVM. It provides methods for Support Vector Machines and related methods, such as One-Clas SVM, nu-SVM...

A program which retrieves TV program data and asks user which TV programs he / she'll watch that day. Using that data program learns the user preferences using machine learning algorithms (such as support vector machines).

Distributed Support Vector Machine

NSvm is a .Net Support Vector Machine library written in .Net. NSvm features the SMO algorithm, a few kernels (including ad hoc algorithms for linear kernels). The objectives of NSvm are simplicity, flexibility and extensibility.

Incridge - A Software Tool for Scalable, Parallel, Incremental and Decremental Classification based on Support Vector Machine (SVM) Approximation Algorithms. Possible use include: web usage mining, bioinformatics and spam-classification.

After the presentation on CeBIT 2004 fair finally available: SpamStop works as a Proxy between your Pop3-Client and the -Provider, it uses a Support Vector Machine to classfy incoming mails and automatically learns classifiers from samples of your mails.

Ruby SVM is a Ruby binding to the very popular and highly useful libsvm library (released under a seperate license) This allows you to effortlessly experiment with machine learning, in particular Support Vector Machines, in Ruby. SVM's have found use in

OSU SVM is a Support Vector Machine (SVM) toolbox for the MATLAB numerical environment. The toolbox is used to create models for regression and classification using support vector machines.

A standalone, STL interface to the Torch library's Support Vector Machine (SVM). It supports single or multiclass (one vs. all) classification using dot product, polynomial, Gaussian and sigmoid kernels.

This project allows the Delta Executor APK to be compatible with Roblox running natively on a Windows PC. Delta Executor For PC emulates the necessary environment to run the APK and integrates it with the Roblox process running on your Windows machine. If the Delta Executor APK is not found, the project will automatically download it. The "DeltaExecutorVector.svg" file is just the logo in vector format. How to run 1. It's good practice to always first read the source code. 2. Click...