$1.)$ Cosmetics Purchases. The data shown in Table $15\mathrm{.}17$ and association rule output in Table $15\mathrm{.}18($both shown below$)$ are based on a subset of a dataset on cosmetic purchases $($mlba::Cosmetics$)$ at a large chain drugstore. The store wants to analyze associations among purchases of these items for purposes of point$-$of$-$sale display, guidance to sales personnel in promoting cross sales, and guidance for piloting an eventual time$-$of$-$purchase electronic recommender system to boost cross sales.

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a$.$ Considering the complete dataset on the cosmetics purchases $($in the dataset mlba::Cosmetics$),$ using R$,$ generate item frequency plot and identify top three items from the data.

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b$.$ Apply association rules to these data and list $10$ rules with top lift. $($Suggested minimum support $0\mathrm{.}2$ and minimum confidence $0\mathrm{.}5.)$

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c$.$ Interpret the first three rules with top lift in the output in words. How can the analysis help the business?