"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count data. The most ...
Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
The latest trends in software development from the Computer Weekly Application Developer Network. This is a guest post for the Computer Weekly Developer Network written by Yana Yelina in her role as ...
The goal of a binary classification problem is to make a prediction that can be one of just two possible values. For example, you might want to predict the sex (male or female) of a person based on ...
A class of conditional logistic regression models for clustered binary data is considered. This includes the polychotomous logistic model of Rosner (1984) as a special case. Properties such as the ...
Dr. James McCaffrey from Microsoft Research presents a C# program that illustrates using the AdaBoost algorithm to perform binary classification for spam detection. Compared to other classification ...
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