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module Y2016.M12.D21.Exercise where
import Data.Array
-- below imports available via @1HaskellADay git repository
import Data.SAIPE.USStates
import Data.SAIPE.USCounties
import Graph.ScoreCard
import Graph.KMeans
{--
So, now that we have the US county data, and as ScoreCard values.
Cluster these data.
--}
data Axes = Population | Poverty
deriving (Eq, Ord, Show, Enum, Bounded, Ix)
clusterSAIPE :: [ScoreCard USCounty Axes Float]
-> SCClusters Int USCounty Axes Float
clusterSAIPE counties = undefined
{--
And do this study:
1) what is the 'optimal'/most-makes-sense number of clusters?
2) what is the most populous cluster, county-population-wise and number of
ScoreCard values-wise? What is the least populous cluster, same criteria?
Further study:
3) what associations do you see? Are there obvious City vs. Country differences?
Other differences that are obvious?
4) Where do major cities fall? Together in one cluster? Or do they appear along
more geographically divided lines?
--}