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 Analys
My primary research interests are concentrated in the areas of bioinformatics, data mining, and parallel processing, and from time-to-time I look at various problems in the areas of information retrieval, collaborative filtering, and electronic design aut
APRIORI algorithm was originally proposed by Agrawal in "Fast Algorithms for Mining Association Rules" in 1994 to find frequent itemsets and association rules in a transaction database. Here you can download a fast, trie-based, command-line implementation
Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, a
A. Agostini, G. Amelino-Camelia, and F. D'Andrea. (2003)cite arxiv:hep-th/0306013
Comment: 20 pages, no figures, LaTex. This version has exactly the same
technical content as version 1, but the observation reported in Section VII
is discussed more pedagogically.
M. Arzano. (2007)cite arxiv:0711.3222
Comment: 13 pages, no figures. To appear in the proceedings of the workshop
"From Quantum to Emergent Gravity: Theory and Phenomenology", Trieste, Italy,
June 11-15 2007.
M. Mariotti. Proceedings of the 22nd Conference of the International Group for the Psychology of Mathematics Education, 1, page 180--195. Stellenbosch, South Africa, PME, University of Stellenbosch, (July 1998)