PROC FASTCLUS is run on a 5-million-row dataset with MAXCLUSTERS=8…

Question

PROC FASTCLUS is run on a 5-million-row dataset with MAXCLUSTERS=8 and MAXITER=20. Which characteristic makes PROC FASTCLUS more efficient than PROC HPCLUS for very large datasets when a fixed number of clusters is required?

Accepted Answer

PROC FASTCLUS is a base SAS procedure that uses a single-pass algorithm with efficient seed selection and reassignment, designed to handle large datasets on single-node SAS without requiring CAS — Here's the deal — b is correct because PROC FASTCLUS is a base SAS procedure optimized for single-node large-dataset k-means clustering. It uses efficient seed selection (farthest-first initialization) and a single-pass initial assignment step before iterative refinement.

Answer

PROC FASTCLUS uses approximate nearest-neighbor search with random seed selection, making it faster at the cost of less accurate seeds compared to PROC HPCLUS's default seed selection

Answer

PROC FASTCLUS parallelizes computation across CAS worker nodes, whereas PROC HPCLUS runs only on a single node

Answer

PROC FASTCLUS uses hierarchical pre-clustering to determine initial seeds, which is more efficient than random initialization

PROC FASTCLUS is run on a 5-million-row dataset with MAXCLUSTERS=8 and MAXITER=20. Which characteristic makes PROC FASTCLUS more efficient than PROC HPCLUS for very large datasets when a fixed number of clusters is required?

Short Explanation and Infographic

Full Explanation