Svm
Solaris::Disk::SVM::Graph is a Perl module for graph your Solaris Volume Manager configurations. SYNOPSIS my $graph = Solaris::Disk::SVM::Graph->new( sourcedir => path/to/dir, # path to SVM config files, # see Solaris::Disk::SVM for details fontname => fontname, fontsize => fontsize, );...
Platforms: *nix
License: Freeware | Size: 11.26 KB | Download (108): Solaris::Disk::SVM::Graph Download |
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
Platforms: *nix
License: Freeware | Size: 30.72 KB | Download (39): Ruby SVM (Support Vector Machines) Download |
SVMs are a bit tricky. In this case, we show a linear SVM and illustrate its behaviour on some 2D data. This should be great for getting to grips with maximising geometric margins, support vectors, and the optimisation involved in computing an optimal separating hyperplane.Data can be generated...
Platforms: Matlab
License: Freeware | Size: 20.48 KB | Download (45): SVM Demo Download |
Iracema is a Named Entity Recognition and Classification (NERC) library that aims to provide algorithms and commonly used functionality for both implementing and evaluating NERC systems. It is implemented in Java. Iracema features: * A Flexible architecture for implementing and evaluating NERC...
Platforms: Mac
License: Freeware | Size: 41.91 MB | Download (41): iracema Download |
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.
Platforms: *nix
License: Freeware | Size: 71.68 KB | Download (34): PiSvM Download |
The Kernel-Machine Library is a freely available (released under the GPL) C++ library to promote the use and progress of kernel machines. It is both for academic use and for developing real world applications. The Kernel-Machine Library draws heavily from features of modern C++ such as template...
Platforms: *nix
License: Freeware | Size: 51.2 KB | Download (107): Kernel-Machine Library Download |
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.
Platforms: Windows, Mac, Linux
License: Freeware | Size: 34.69 KB | Download (49): Feating Download |
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
Platforms: Windows, Mac, Linux
License: Freeware | Size: 849.38 KB | Download (48): Stalk: an OO language Download |
This applicationĀ is an open-source machine learning program for supervised classification of patterns (vectors of measurements). PCP implements the following algorithms and methods: - Fisher's linear discriminant - dimensionality reduction using Singular Value Decomposition - Principal...
Platforms: Windows, Mac, *nix, C/C++, BSD Solaris
License: Freeware | Download (59): PCP Application Download |
This demo gives a clear visual presentation of what happens during the Adaboost algorithms. It shows how the decision boundary, example weights, training error and base learner weights change during training.A selection of base learning algorithms are included: Linear Regression, Naive Bayes,...
Platforms: Matlab
License: Freeware | Size: 10 KB | Download (56): Boosting Demo Download |
The large classification margin is the most usual approach to achieve good generalization. The most known maximal margin algorithm is SVM, for which different kernels have been investigated. Unfortunately, in the context of some real world problems, such as on-the-fly object detection, the use of...
Platforms: Matlab
License: Freeware | Size: 10 KB | Download (39): MMGDX: a maximum-margin training method for neural networks Download |
MultiViL is a tool for multi-view learning. It supports four classifiers (KNN, Naive-Bayes, Rochio and SVM-Perf), four view combining methods (Majority Voting, Borda Count, Dempster-Shafer theory of evidence and PSO) and provides many analisys tools.
Platforms: *nix
License: Freeware | Size: 4.16 MB | Download (40): MultiViL Download |