You have a data set with the following variables: Household income, which runs from $30,000 to $120,000 Number of children in family, from 0 to 5 Number of years in current location, from 0 to 20+ Whether they rent or own, as a text field Number of miles driven per year, from 0 to 50,000 Population in their location, from 100 to 1 million + Where possible, you have standardized the variables, and you have recoded the rent/own text field into a binary 0 (for rent) and 1 (for own). You want to run a k-means algorithm on this entire data set, to try to determine different demographic niches. For example, you may want to separate out urban apartment-dwellers from rural retirees. Is it possible to run k-means clustering on all of these data fields? Say you have loaded the standardized variables above into columns 1 through 6 in a data frame called responses. Let’s say you want to try for 7 clusters. In particular, can you do something like this? > fit
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