One-hot encoding is a prevalent method used to convert numeric variables into categorical variables. But one-hot encoding omits crucial quantitative data, which compromises the performance of ...

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...

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 = ...