Classifiers

Fast implementation of the GRLVQ, SRNG and H2MGLVQ algorithms, three supervised LVQ classifiersPlease run mexme_NN to recompile mex files on your own plateformPlease run test*.m to run demos

The Linux QoS Library (LQL) provides a GPL licensed, GObject based C API to manipulate the network queueing disciplines, classes and classifiers in the Linux kernel. LQL does not use the TC command as a back-end. Instead, LQL communicates with the Linux kernel via Netlink sockets the same way...

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.


Platforms: Windows, Mac, Linux

The GUI executes various WEKA classifiers and displays the results in MATLAB. Key features "mweka": - Command line options for running weka - Demonstrate how to change classifier option using java class (similiar to GenericObjectEditor in weka) - Read and Write ARFF file to/from MATLAB - Able to...


Platforms: Windows, Mac, *nix, Matlab, BSD Solaris

Modular toolkit for Data Processing (MDP) is a Python data processing framework. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Growing Neural Gas (GNG), Factor Analysis, Fisher Discriminant Analysis (FDA),...


Platforms: Windows, Mac, *nix, Python, BSD Solaris

It is known that there is no sufficient Matlab program about neuro-fuzzy classifiers. Generally, ANFIS is used as classifier. ANFIS is a function approximator program. But, the usage of ANFIS for classifications is unfavorable. For example, there are three classes, and labeled as 1, 2 and 3. The...


Platforms: Matlab

Decreasing the individual error and increasing the diversity among classifiers are two crucial factors for improving ensemble performances. Nevertheless, the d-deDUkappa-errord-deDt diagram shows that enhancing the diversity is at the expense of reducing individual accuracy. Hence, We proposed...


Platforms: Matlab

This little package contains a Parzen Neural Network classifier that can classify data between N classes in D dimensions. The classifier is really fast and simple to learn. The good classification performance can be obtained for a certain class of data distributions. Other classifiers must be...


Platforms: Matlab

PyML is an interactive object oriented framework for machine learning written in Python. PyML focuses on SVMs and other kernel methods. It is tested on Linux and Mac OS X. Features?*A* * Classifiers: support vector machines, nearest neighbor, ridge regression * Multi-class methods...


Platforms: Mac

PyML is an interactive object oriented framework for machine learning written in python. PyML focuses on kernel classifiers, providing tools for feature selection, model selection, and methods for assessing classifier performance.


Platforms: *nix

Matlab Classification Toolbox contains implementations of the following classifiers: Naive Bayes, Gaussian, Gaussian Mixture Model, Decision Tree and Neural Networks. This toolbox allows users to compare classifiers across various data sets.


Platforms: *nix

phpTCadmin is Web based interface administration QoS on Linux. A Traffic Control interface. Currently it can: create queue disciplines to all algoritms, create class to all classfull algoritms, put all qdisc inside classes, create classifiers with u32.


Platforms: *nix

The LTI-Lib is an object oriented library with algorithms and data structures frequently used in image processing and computer vision. The main goal of the LTI-Lib is to provide an object oriented library in C , which simplifies the code sharing and maintenance, but still providing fast...


Platforms: Windows, Mac, *nix, C/C++, BSD Solaris

iptables and netfilter are building blocks of a framework inside the Linux 2.4.x and 2.6.x kernel. This framework enables packet filtering, network addresss [and port] translation (NA[P]T) and other packet mangling. It is the re-designed and heavily improved successor of the previous Linux 2.2.x...


Platforms: *nix

Xholon runtime framework executes applications that are event-driven or that have highly dynamic structure or behavior. Specify your models using XML and Java, or using third-party UML2 tools and MDA transformations. To get started, read or actively work through the basic HelloWorld tutorial....


Platforms: *nix

MACTS project is a traffic shaper that uses MAC addresses which are associated with users to classify traffic. This allows fair usage of bandwidth among many machines. Additionally, there is a statistics monitor which displays current statistics on the terminal or stores them in round robin...


Platforms: *nix

ECOC PAK was built to act as a C++ library for the Error Correcting Output Codes classification framework. It supports several coding and decoding strategies as well as several classifiers. ECOC PAK aims to give the researchers of the Machine Learning Community a free and efficient tool for the...


Platforms: Windows

Weka is a complete and user-friendly data-mining environment that can be used for any research project. But Weka decision tree classifiers outputs the decision tree either as a Weka-syntaxed text tree or as a binary file (neither readable nor editable in a text editor).


Platforms: Windows

The Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex...


Platforms: Windows, Mac, Linux

A Linux Traffic Control Management Interface: build tc-style rules for control network flows. Have support to set queue disciplines to interface (root) or inside a class (leaf), create classes and classifiers.


Platforms: Windows, Mac, Linux