The following links point to a set of tutorial slides by Andrew Moore on many aspects of statistical data mining, including the foundations of probability, the foundations of statistical data analysis, and most of the classic machine learning and data mining algorithms. These include classification algorithms such as decision trees, neural nets, Bayesian classifiers, Support Vector Machines and cased-based (aka non-parametric) learning. They include regression algorithms such as multivariate polynomial regression, MARS, Locally Weighted Regression, GMDH and neural nets. And they include other data mining operations such as clustering (mixture models, k-means and hierarchical), Bayesian networks and Reinforcement Learning. This has been added to Data Mining Resources Subject Tracer™ Information Blog. This has been added to Tutorial Resources Subject Tracer™ Information Blog. This has been added to Statistical Resources Subject Tracer™ Information Blog.
posted by Marcus Zillman |
4:00 AM
