High-level data classification techniques are capable of considering not only physical aspects of the data, such as space, distance, proximity, distribution, but can also consider their functional, ...

Classification algorithms are widely used in data science to predict the category or label of a given ... random search, or Bayesian optimization, that vary in their efficiency and complexity ...

Particle Swarm Optimization algorithm for detecting forged banknotes. The task Particle Swarm Optimization algorithm was used in order to learn weights for multiplayer perceptron neural network for ...

K-nearest neighbor (K-NN) algorithm is a classification method based on statistical theory. In this algorithm the Euclidean distance is usually chosen as the similarity measure, which usually relates ...

To evaluate the diagnostic accuracy of an algorithm, it can be compared to the best existing classification for the used dataset, for which the value 100 percent is assigned.

Optimization of classification model for electric vehicle charging station placement using dynamic graylag goose algorithm. Amel Ali Alhussan 1 * Doaa Sami Khafaga 1 El-Sayed M. El-kenawy 2,3 Marwa M.

Keywords: environmental issues, rainfall, guided whale optimization algorithm, adaptive dynamic puma optimizer, voting ensemble, forecasting, classification. Citation: Elkenawy E-SM, Alhussan AA, Eid ...