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 Platforms: Matlab

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... Platforms: *nix

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

Weka is a comprehensive open source Machine Learning toolkit, written in Java at the University of Waikato, New Zealand. These functions provide a basic Matlab interface to Weka allowing you to transfer data back and forth and access major Weka features, such as training Classifiers. They have... Platforms: Matlab

I noticed most people here used OpenCV in MATLAB and said they did face detection. Those who did it by themselves had a bunch of code that was not understandable. I made a website www.ece301.com which explains in detail my code for face detection using matlab so that people can get an idea of... Platforms: Matlab

This code is provides a simple introduction to some of the Classification capabilities in Statistics Toolbox. Key techniques used includeUsing normplot to see whether features are normally distributed.Using coercoff to look for correlation between features.Using cvpartion to separate data into a... Platforms: Matlab

The High Dimensional Data Clustering (HDDC) toolbox contains an efficient unsupervised classifiers for high-dimensional data. This classifier is based on Gaussian models adapted for high-dimensional data.Reference: C. Bouveyron, S. Girard and C. Schmid, High-Dimensional Data Clustering,... Platforms: Matlab

This M-file focuses on a 3-class pattern classification problem. It generates hundred random samples for each pattern class using given parameters for the class-conditional densities. Further the Gaussian classifier is implemented to classify test samples of each class using equal prior class... Platforms: Matlab

This program calculates the Euclidean distances of every possible pair of points, whose coordinates are given as rows in a matrix. It is particularly useful for distance-based classifiers, due to its limited computational cost. The program can be easily adapted to calculate Manhattan distance or... Platforms: Matlab

scala-recog is a library written in Scala to provide general implementations of machine learning algorithms. Features Classifiers k-NN ID3: see Decision Tree example Bayes: see Bayes example Logistic Regression: see Logistic Regression Traits Platforms: Mac

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

Stanford NER (also known as CRFClassifier) is a Java implementation of a Named Entity Recognizer. Named Entity Recognition (NER) labels sequences of words in a text which are the names of things, such as person and company names, or gene and protein names. The software provides a general... 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