Northern Goshawk Optimization (NGO) is a recently proposed swarm-based optimization method that hunts like a northern goshawk. However, while the approach excels with many benchmark functions, it is incapable of deali...
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Northern Goshawk Optimization (NGO) is a recently proposed swarm-based optimization method that hunts like a northern goshawk. However, while the approach excels with many benchmark functions, it is incapable of dealing with the binary optimization problem. We proposed a binary variation of NGO for feature selection (FS) issues in classification tasks. We employed S and V-shaped transfer functions (TF) to convert continuous data to binary values. The suggested model is evaluated based on six high dimensional microarray cancer datasets using the benchmark evaluation measures such as accuracy, fitness and number of features selected. To demonstrate the effectiveness of the suggested model, it is compared to traditional and recent binary versions metaheuristic algorithms. According to the findings, the S-shaped transfer function surpasses other transfer functions and classical models.
In recent years, a significant number of deaths worldwide have been due to cancer. Analysis of microarray gene expression data facilitates early cancer identification. The accurate discovery of information for thousan...
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