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Related Questions
- Can over-clustering compromise the validity of cluster findings and what are the key symptoms?
- Does over-clustering yield fewer distinct clusters or worse stability across different clustering settings than under-clustering do, why?
- Is there a technique like Elbow method and silhouette method that can objectively resolve this trade-off against criteria, such as separation distance?
- At what point does it no longer make sense for research objectives to have large no of clusters and become unrealistic with too much distinct variables for analysis?
- Can over-agglomeration and fragmented into micro-clusters contribute or counteract to increased statistical validity?
- When is the situation over-simplification would create confusion in interpreting significant but over-simplified factor cluster.
- For different types of problem context is there an adaptive statistical metric that would signal researchers, when it over -simplified, thereby sacrificing more nuanced relationships inherent into datasets.
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