Discretization algorithms serve as a critical pre-processing step within data mining and machine learning, transforming continuous attributes into discrete categories to enhance the interpretability ...

Learn how to discretize data in a mining model, which involves putting values into buckets so that there are a limited number of possible states. In these cases, you can discretize the data in the ...

Abstract: Discretization is an essential preprocessing technique used in many knowledge discovery and data mining tasks. Its main goal is to transform a set of continuous attributes into discrete ones ...

Creating robust and explainable statistical learning models is essential in credit risk management. For this purpose, equally spaced or frequent discretization is the de facto choice when building ...

Abstract: The optimal path planning problems are very difficult for some of the generalized weighted region shortest path problems, where the cost metric varies not only in different regions of the ...

Two methods of discretization of the s-wave n-p breakup continuum are compared, and their effect on the elastic deuteron-nucleus scattering matrix elements is numerically investigated. In one of the ...