library(stats)
data(wetland) ## Loads species data
## Creates three clusters using kmeans
wetkm <- kmeans(wetland, centers=3)
## Run indicator analysis with species combinations for the first group
sc <- indicators(X=wetland, cluster=wetkm$cluster, group=1, verbose=TRUE, At=0.5, Bt=0.2)
## Finds the 'best' subset of indicators
sc2 <- pruneindicators(sc, At=0.5, Bt=0.2, verbose=TRUE)
print(sc2)
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