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Logistic regression

Known as: Regression, Binary logit model, Conditional logistic regression 
In statistics, logistic regression, or logit regression, or logit model is a regression model where the dependent variable (DV) is categorical. This… Expand
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Highly Cited
2008
Highly Cited
2008
The group lasso is an extension of the lasso to do variable selection on (predefined) groups of variables in linear regression… Expand
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Highly Cited
2007
Highly Cited
2007
Logistic regression analysis of high-dimensional data, such as natural language text, poses computational and statistical… Expand
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Highly Cited
2001
Highly Cited
2001
We study rare events data, binary dependent variables with dozens to thousands of times fewer ones (events, such as wars, vetoes… Expand
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Highly Cited
2001
Highly Cited
2001
We compare discriminative and generative learning as typified by logistic regression and naive Bayes. We show, contrary to a… Expand
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Highly Cited
2000
Highly Cited
2000
The Logic of Logistic Regression Interpreting Logistic Regression Coefficients Estimation and Model Fit Probit Analysis… Expand
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Highly Cited
1999
Highly Cited
1999
From the Publisher: If you are a researcher or student with experience in multiple linear regression and want to learn about… Expand
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Highly Cited
1999
Highly Cited
1999
If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression… Expand
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Highly Cited
1989
Highly Cited
1989
Introduction to the Logistic Regression Model Multiple Logistic Regression Interpretation of the Fitted Logistic Regression Model… Expand
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Highly Cited
1988
Highly Cited
1988
Abstract We discuss the use of standard logistic regression techniques to estimate hazard rates and survival curves from censored… Expand
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Highly Cited
1978
Highly Cited
1978
Abstract Classifying an observation into one of several populations is discriminant analysis, or classification. Relating… Expand
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