The store wants to analyze associations among purchases of these items for purposes of pointof$-$sale display, guidance to sales personnel in promoting crosssales, and guidance for piloting

an eventual time$-$of$-$purchase electronic recommender system to boost cross$-$sales.

$1.$ Download a data file $("$Cosmetics$\_$new.csv $")$ and read the file as cosmetics$.$df$.$ Report dim$().$

$2.$ Convert cosmetics$.$df into a matrix named cosmetics$.$mat. Remove the first column not

necessary for analyzing data using association rules. Report the max value of each of the

columns in the matrix.

$3.$ If necessary, convert cosmetics$.$mat into a binary incidence matrix named bin.cosmetics$.$mat

so that the max value in the matrix would be $1.$ Report the max value of each of the columns in

the matrix.

$4.$ Plot frequency $($support$)$ for single Items.

$5.$ Using inspect$(),$ report frequent itemsets with the following parameter values: supp$=0\mathrm{.}20.$

When generating the itemsets, remove single itemsets.

$6.$ Using inspect$(),$ report association rules with the following parameter values: supp$=0\mathrm{.}20,$

conf $=0\mathrm{.}5.$ When generating the itemsets, remove single itemsets. Display the rules in the

descending order by lift.

$7.$ Interpret the first two of the resulting rules, in terms of confidence and lift. Add text at the end

of the Word file for answering this question.

Create your assignment report $($Word file$)$ using RMarkdown. Submit the Word file along with the script

$(.$R$)$ file to LearnUS.