Research Article

A Distributed Algorithm for the Cluster-Based Outlier Detection Using Unsupervised Extreme Learning Machines

Algorithm 2

CB outlier detection on each slave node.
Input. The cluster set reserved on slave node , integers , , the threshold
Output. The CB outliers in
() for each cluster in do
()   Sort the points in according to the distances to the centroid point
    in ascending order;
()   Scan the points in reversed order;
()   for each scanned point do
()    Initialize a heap ; // to reserve the current NNs of
()    ; // the largest distance from the points in to
()   boolean = true;
()   Visit the points from to the both sides to search ’s NNs;
()   for each visited point do
()      if is before and
        then
()       Erase the points before from the visited list;
()      else if is behind and
        then
()       Erase the points behind from the visited list;
()      else
()       Update and ;
()      if meets the condition of Corollary 5 then
()        = false;
()       break
()    if then
()     Send to the master node to update ;