New method revolutionizes outlier detection in data mining tasks.
Outlier detection is important in data mining. A new method using neighborhood-based techniques was developed to find and analyze outliers. By looking at the weights of nearby data points and using a special parameter called OBN, outliers were identified. The algorithm was tested on real data and compared to existing methods, showing promising results.