Which data mining techniques do you use regularly (Oct 2002)

Poll

Which data mining techniques do you use regularly? (Choose several) [212 votes, 825 choices] Decision Trees/Rules (128) 16% Clustering (103) 12% Statistics (101) 12% Logistic regression (75) 9% Neural networks (75) 9% Association rules (63) 8% Visualization (52) 6% Nearest neighbor (42) 5% Text mining (30) 4% Sequence analysis (27) 3% Genetic algorithms (26) 3% Bayesian nets (24) 3% Hybrid methods (21) 3% Naive Bayes (19) 2% Web mining (19) 2% Other (20) 2%

Comments

J.P.Brown, SuperInduction
The list of techniques that people could be using was wide-ranging, but the list that I am offering includes some others.
Keeping it simple, my list includes:
Statistics; Probability Scale; Classification; Neural Nets & Clementine

Bruno Delahaye, Others: Techniques using SRM
Vapnik's theory 'Structured Risk Minimisation' (SRM) allows to transform traditionnal algorithms into robust algorithms. For instance KXEN has implemented "Robust Regression" (for regression and classification) i.e SRM applied to polynomial functions.

Krzysztof Cios, hybrid methods
hybrid methods are, for example, methods which are a combination of rule machine learning algorithms and decision tree learning algorithms (like CLIP3 or CN2)