A binary classification model usually outputs a probability score between 0 and 1 for each input, and then applies a threshold to decide which class to assign. For example, ...

Our work proposes preliminary inroads in two main directions: (a) proposing a SAT-based model for computing a decision tree as the smallest Reduced Ordered Binary Decision Diagram, consistent with ...

The attributes are binary and are presented in a sparse matrix format within train.dat and test.dat. train.dat: Training set (a sparse binary matrix, patterns in lines, features in columns, with class ...

This code implements a binary image classification model using the pre-trained VGG-16 architecture. The model is fine-tuned for a specific binary classification task, such as distinguishing between ...

A number of known models are often regarded as interpretable by human decision makers with varying degrees of difficulty. The size of such models plays a crucial role in determining how easily they ...