"Phil Sherrod" <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>... > I'm doing research comparing boosted decision trees to neural networks for > various types of predictive analyses. A boosted decision tree is an > ensemble tree created as a series of small trees that form an additive > model. I'm using the TreeBoost method of boosting to generate the decision > tree series. TreeBoost uses stochastic gradient boosting to increase the > predictive accuracy of decision tree models (see > http://www.dtreg.com/treeboost.htm).
The standard place to look for data that has been used in a wide variety of contexts is the UCI machine learning repository. You should be able to find any number of papers detailing any number of http://www.ics.uci.edu/~mlearn/MLRepository.html Also, are you using the WEKA (Waikato Environment for Knowledge Analysis). This is a toolbox with a number of machine learning algorithms and built in functions for evaluating the accuracy of algorithms. Providing that you stick to the arff format or can convert your data into it (not difficult) you can compare your results with the results of all the other algorithms in the toolbox. http://www.cs.waikato.ac.nz/ml/weka/ Cheers, Ross-c . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
