In a survey, the following data was collected.□ Among 5000 teenagers who wear jeans,o 3000 play on-line gameso 3750 eat chipso 2000 both play on-line games and eat chips□ Among another 5000 teenagers who do not wear jeans,o 3000 play on-line gameso 4000 eat chipso 2250 both play on-line games and eat chipsa) List ALL strong association rules having the form {item1, item2eat chips} with support15% and confidence50%.b) Compute the interest (lift ratio) of the strong association rules found in part (a).

In a survey, the following data was collected. □ Among 5000 teenagers who wear jeans, o 3000 play on-line games o 3750 eat chips o 2000 both play on-line games and eat chips □ Among another 5000 teenagers who do not wear jeans, o 3000 play on-line games o 4000 eat chips o 2250 both play on-line games and eat chips a) List ALL strong association rules having the form {item1, item2＝>eat chips} with support=>20% and confidence=>50%.

In data mining, what does the lift measure in association rules?Answer choicesSelect only one optionREVISITThe strength of the relationship between itemsThe support of an itemsetThe confidence of a ruleThe improvement of prediction over random guessing

calculate lift, leverage, and conviction of an association rule.

What does the lift ratio measure in the context of association rules? (Antecedent is left hand side itemset, Consequent is right hand side itemset)Group of answer choicesThe accuracy of the association between the antecedent and consequent in an association rule.The support of the antecedent and consequent in an association rule.The confidence of the antecedent and consequent in an association rule.The improvement of finding the consequent when the antecedent is known compared to random chance.

: Design algorithms for association rule mining algorithms