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 ...

Abstract: Many machine learning algorithms can be applied only to data described by categorical attributes. So discretization of continuous attributes is one of the important steps in preprocessing of ...

Abstract: This study examines the use of greedy algorithms, dynamic programming algorithms, and lattice discretization algorithms for solving optimal solutions in practical scientific and engineering ...

(Jena, Germany) Doing pioneer work in science and answering questions of the future--these are tasks of young researchers that the European Research Council (ERC) supports with ERC Starting Grants.

This repository contains the code for experiments in the Master Thesis "State Space Discretization for Reinforcement Learning". The thesis aimed at creating models that transform continuous, ...

Precise detection of PD is important in its early stages. Precise result can be achieved through data mining, classification techniques such as Naive Bayes, support vector machine (SVM), multilayer ...

Simulation of high-fidelity models of extreme fast charging (XFC) systems and large-area power grids with many XFCs can be time consuming in traditional simulators. Traditional simulators use a single ...