The strategy of outlier detection technologies based on the clustering algorithm is focused on the relation between data objects and clusters.
Outlier detection that uses the hierarchical clustering algorithm is based on the k-Nearest Neighbor graph. The input parameters include the input dataset,
DATA, of size,
n, and each data point with
k variables, the distance measure function (
d), one hierarchical algorithm (
h), threshold (
t), and cluster number (
The process of the outlier detection based on the k-means algorithm is illustrated ...