OCC algorithms typically rely on statistical methods or distance metrics, such as the traditional density-based Local Outlier Factor (LOF) Consequently, these approaches generate outcomes that are more straightforward to interpret and subject to in-depth analysis. Moreover, traditional models often exhibit low computational complexity, making them highly efficient and well-suited for handling small dataset. However, it should be noted that these models have two distinct disadvantages.