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Binomial logistic regression, where the outcome is binary (e.g. death, yes/no) is often simply referred to as logistic regression and will be the focus of this article. For example, a team of medical ...

Logistic regression is a technique used to make predictions in situations where the item to predict can take one of just two possible values. For example, you might want to predict the credit ...

Logistic regression is one of many machine learning techniques for binary classification -- predicting one of two possible discrete values. An example is predicting if a hospital patient is male or ...

In the worked example we already considered above, if we run the multiple linear regression, we would generate a 95% confidence interval (CI) around the regression coefficient for age, which is a ...

The model can naturally account for sampling variabilities and zero observations and also allow for a flexible covariance structure among the bacterial taxa. In order to select the relevant covariates ...

A machine learning model may help predict mortality for hospitalized patients with cirrhosis at the time of admission, ...

This article derives a new family of estimators, namely the minimum density power divergence estimators, as a robust generalization of the maximum likelihood estimator for the polytomous logistic ...