R: Data Analysis and Visualization

Intrusion detection and clustering-based methods

The strategy of outlier detection technologies based on the clustering algorithm is focused on the relation between data objects and clusters.

Hierarchical clustering to detect outliers

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 (nc).

The k-means-based algorithm

The process of the outlier detection based on the k-means algorithm is illustrated ...