Selecting the most relevant subset of features from a dataset is vital step in data mining and machine learning. Each feature has 2n possible subsets, making it challenging to select optimum collection using typical methods. As result, new metaheuristics-based selection method based on dipper-throated grey-wolf optimization (DTO-GW) algorithms been developed this research. Instability can resul...

Exploration and exploitation are two essential components for any optimization algorithm. Much exploration leads to oscillation and premature convergence while too much exploitation slows down the optimization algorithm and the optimizer may be stuck in local minima. Therefore, balancing the rates of exploration and exploitation at the optimization lifetime is a challenge. This study evaluates ...

Spam is an unwanted email that is harmful to communications around the world. Spam leads to a growing problem in a personal email, so it would be essential to detect it. Machine learning is very useful to solve this problem as it shows good results in order to learn all the requisite patterns for classification due to its adaptive existence. Nonetheless, in spam detection, there are a large num...