Search Results for "http-client" - Page 3

This project implements the techniques used in this paper: @INPROCEEDINGS{Andres10a, author = {Jesús Andrés-Ferrer and Germán Sanchis-Trilles and Francisco Casacuberta}, title = {Similarity Word-Sequence Kernels for Sentence Clustering}, booktitle = {Proceedings of the 8th International Workshop on Statistical Pattern Recognition}, year = {2010}, } This project depends on jaf_Utils: http://sourceforge.net/projects/jafutils/ Install it prior installation of jaf_Kernels.

This project contains weka packages of neural networks algorithms implementations like Learning Vector Quantizer (LVQ) and Self-organizing Maps (SOM). For more information about weka, please visit http://www.cs.waikato.ac.nz/~ml/weka/

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.

This is an attempt to create simple image recognition program in java. Demo here: http://www.youtube.com/watch?v=N4m4j4D3pJU

Very basic cellular automaton implementation in C#. Based upon the "Togetherness" algorithm described at http://www.hermetic.ch/pca/tg.htm.

Highly reusable and extensible Decision-Tree (Max-Gain) framework comprising of comprehensive input-processing and display functionality. Handles nominal, linear, continuous data. For preliminary description, refer - http://sushain.com/blog/archives/

pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. 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...

...This data is used for classification and is the subject of the category-based analysis. Cinefile was developed by the University of Mary Washington's Computer Science department (http://cas.umw.edu/computerscience).