Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

The most commonly used statistical models of civil war onset fail to correctly predict most occurrences of this rare event in out-of-sample data. Statistical methods for the analysis of binary data, ...

We introduce a method for learning pairwise interactions in a linear regression or logistic regression model in a manner that satisfies strong hierarchy: whenever an interaction is estimated to be ...

Logistic regression was developed starting in the late 1930s as an effort to improve a binary classification technique called probit regression. Even though several more recently developed techniques, ...