The performance of search engines crucially depends on their ability to capture the meaning of a query most likely intended by the user. We study the problem of mapping a search engine query to those nodes of a given subject taxonomy that characterize its most likely meanings. We describe the architecture of a classification system that uses a web directory… (More)
There is a substantial disagreement in the existing literature regarding which hemisphere of the brain controls spatial abilities. In an attempt to resolve this dispute, we conducted a meta-analysis to decipher which hemisphere truly dominates and under what circumstances. It was found that across people and situations, the right hemisphere is the more… (More)
Most decision tree algorithms base their splitting decisions on a piecewise constant model. Often these splitting algorithms are extrapolated to trees with non-constant models at the leaf nodes. The motivation behind Look-ahead Linear Regression Trees (LLRT) is that out of all the methods proposed to date, there has been no scalable approach to exhaustively… (More)
In this paper, we describe techniques that can be used to predict the effects of gene deletion. We will focus mainly on the creation of predictive variables, and then briefly discuss different modeling techniques that have been used successfully on this data.
This 2004 KDD Cup presents a perfect case where the usual neural network objective functions do not apply. While the contest problem consisted of 4 different entries with 4 different objective functions, this paper will focus on the solution optimizing GRMSE (Grouped Root Mean Squared Error). It will be shown that the more typical objective functions… (More)
What is the difference between matter and anti-matter? A. I. Insight's winning solution on the Particle Physics Task for the 2004 KDD Cup demonstrates how an accurate predictive model can be formulated without knowledge of the content of the data. Information on the data was not available for the modeling, including a description on the outcome to be… (More)
Transformation of both the response variable and the predictors is commonly used in fitting regression models. However, these transformation methods do not always provide the maximum linear correlation between the response variable and the predictors, especially when there are non-linear relationships between predictors and the response such as the medical… (More)