Feature selection is a preprocessing technique frequently used in data mining and machine learning tasks. It can reduce dimensionality, remove irrelevant data, increase learning accuracy, and improve results comprehensibility. FCBF is a fast correlation-based filter algorithm designed for high-dimensional data and has been shown effective in removing both irrelevant features and redundant features