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TitleThe Independent Sign Bias: Gaining Insight from Multiple Linear Regression
NamePazzani, Michael John (Author), Bay, Stephen D. (Author),
Date Created1999
SubjectRegression analysis,
Log-linear models
DescriptionAs electronic data becomes widely available, the need for tools that help people gain insight from data has arisen. A variety of techniques from statistics, machine learning, and neural networks have been applied to databases in the hopes of mining knowledge
from data. Multiple regression is one such method for modeling the relationship between a set of explanatory variables and a dependent variable by fitting a linear equation to observed data. Here, we investigate and discuss some factors that influence whether the resulting regression equation is a credible model of the
data.
from data. Multiple regression is one such method for modeling the relationship between a set of explanatory variables and a dependent variable by fitting a linear equation to observed data. Here, we investigate and discuss some factors that influence whether the resulting regression equation is a credible model of the
data.
NotePazzani, Michael J. and Bay, Stephen D. (1999). "The Indepdendent Sign Bias: Gaining Insight from Multiple Linear Regression" Proceedings of the Twenty First Annual Conference of the Cognitive Science Society.
NoteThis research was funded in part by the National Science
Foundation grant IRI-9713990.
Foundation grant IRI-9713990.
Genrearticles
Persistent URLhttp://hdl.rutgers.edu/1782.1/rucore30016700001.Manuscript.000056844
LanguageEnglish
CollectionPazzani Michael Collection
Organization NameRutgers, The State University of New Jersey
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