Binary Classification Using a scikit Decision Tree Dr. James McCaffrey of Microsoft Research says decision trees are useful for relatively small datasets and when the trained model must be easily ...

A binary classification problem is one where the goal is to predict a discrete variable that has exactly two possible values. For example, you might want to predict a person's sex (male or female) ...

The four prediction outcomes consisted of three of the most common irAEs and OS as an effectiveness proxy. Binary outcome labels were created using a 1-year time window since most toxicity events ...

The results show that a regression model accurately predicts visual acuity at 3 and 5 years, and a binary classification model can predict and visualize the risk at 5 years for individual patients ...

Sufficient dimension reduction is popular for reducing data dimensionality without stringent model assumptions. However, most existing methods may work poorly for binary classification.