A wave of pseudoscientific papers has tried to dismantle one of biology’s most fundamental truths: only two sexes exist, male and female. These papers often claim that sex is a broad “spectrum,” and ...

Binary cross-entropy (BCE) is the default loss function for binary classification—but it breaks down badly on imbalanced datasets. The reason is subtle but important: BCE weighs mistakes from both ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Biological sex is usually described in simple binary terms: male or female. This works well for germ cells (sperm versus eggs), but for other body organs it is of little help. A new study by the Max ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

Abstract: We consider a human-automation team jointly solving binary classification tasks over multiple time stages. At each stage, the automation observes the data for a batch of classification tasks ...

This package requires only a standard computer with enough RAM to support the in-memory operations. Models were trained on a NVIDIA Tesla V100 from the BWUniCluster 2.0. This is a demo of the best ...

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...

Abstract: Class imbalance poses a critical challenge in binary classification problems, particularly when rare but significant events are underrepresented in the training set. While traditional ...