Search Results for "svm"

Machine-Learning is a repository focused on practical machine learning implementations in Python, covering classic algorithms like k-Nearest Neighbors, decision trees, naive Bayes, logistic regression, support vector machines, linear and tree-based regressions, and likely corresponding code examples and documentation. It targets learners or practitioners who want to understand and implement ML algorithms from scratch or via standard libraries, gaining hands-on experience rather than relying...

...- Support for the Intel and AT&T syntax - An instruction renderer - An instruction parser - Instructions represented as generic models - UNIX/GNU/Linux and Windows support - Portable - written entirely in C (no external dependencies) - C++ wrapper - Supported instruction sets: MMX, 3D-Now!, SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, SSE4A, AVX, AVX2, AES, TBM, BMI1, BMI2, HLE, ADX, CLMUL, RDRAND, RDSEED, FMA, FMA4, LWP, SVM, XOP, VMX, SMX, AVX-512 Source code moved to: https://github.com/swojtasiak/fcml-lib

A set of java programs that extract coordinate and chemical information from PDB files. The binding site regions are extracted using grid based scheme. For binding site, spatio-chemical descriptor is generated based on PocketMatch algorithm of Dr. Kalidas (author of this project too).

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.

The package provides SVM models to be used with SVMlight (http://svmlight.joachims.org/) for drawing a consensus out of individual 3rd-party predictions about the effect of mutations. The 3rd party tools are SIFT, Polyphen2, SNPs&GO and Mutation Assessor. The package also provides a series of Perl modules and scripts to assist in the preparation of data.

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

This RapidMiner-plugin consists of operators for feature selection and classification - mainly on high-dimensional (microarray-) data - and some helper-classes/operators.

Feating constructs a classification ensemble comprising a set of local models. It is effective at reducing the error of both stable and unstable learners, including SVM. For details see the paper at http://dx.doi.org/10.1007/s10994-010-5224-5.

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...

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.

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

This addon is being developed by SVM for a CMS called Coranto at http://coranto.gweilo.org/. This addon will allow you to have a WYSIWYG editor in your news posts. The intent of this addon is to continue the work of kriko and AreoSoul on WebWriter

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.

Stalk is a new prototyping, message-passing OO language similar to Self. The interpreter compiles source text to bytecode for the Stalk Virtual Machine (SVM) and caches it. Compilable on most systems with sane C++ compilers, stalk has optional gtk binding

...Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface. ...

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.