Data is high dimensional with a mix of categorical and continuous attributes.
1. Normal data instances belong to a cluster, while anomalies are not involved.
When the number of clusters is fixed to k, k-means clustering aims to partition n observations into k clusters.
True negatives (tn): Samples in your data, which you classified as not belonging to your class correctly.