Anomaly Detection in Business Process Event Using KNN Algorithm

Process mining deals with data analysis of a specific kind, namely data extracted from the execution of business processes. The investigation of such data may be influenced by outliers suggesting rare behavior or “noise.” in the method of process discovery. This results in occasional journey directions, which clutch the process model in-process exploration, where a process model is automatically derived from the data. It presents this essay with an intuitive approach for extracting unusual activity from case records. The proposed method is tested in-depth. Its implementation dramatically increases the discovered process model efficiency combined with some current process discovery algorithms and scales well to large data sets.