x̄ (using the squared Euclidean distance).
2. Find the most distant record xs from the record xr considered in the previous step.
3. Form two groups around xr and xs, respectively. One group contains xr and the k – 1 records closest to xr. The other group contains xs and the k – 1 records closest to xs.
4. If there are at least 3k records which do not belong to any of the two groups formed in Step 3, go to Step 1 taking as new data set the previous data set minus the groups formed in the last instance of Step 3.
5. If there are between 3k – 1 and 2k records which do not belong to any of the two groups formed in Step 3: a) compute the average record x of the remaining records; b) find the most distant record xr from x̄ c) form a group containing xr and the k – 1 records closest to xr; d) form another group containing the rest of records. Exit the algorithm.
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