Data mining question

Suppose a tweet is represented as a tuple (tweet id, Boolean Boolean). The second Boolean element will be True if the tweet Imatches Twitter REST API Query othcrwise, it will be Falsc. The third Boolcan element will be True if the twcet content is positive trelevant to the topie of interest); Otherwise, it will be False. The whole twitter spacc is represented as the set of tweets: Suppose the crawled tweets using Twitter REST API Query is represented as the set of tweets: M -t(2, True, False), (3, True Truc), (6, True, True), (9, Truc, False), (14, True, Falsc)) Suppose the set of tweets from randomly sampled users is: D' 1(1, False, False), (4, True, True), (6, True, True), (9, True, False) (10, Falsc, Truc), (12, True, Falsc), (18, True, Falsc), (14, True, Fals (15, True, Truc)) Give the above sampled tweets, calculate the approximate values of the three metrics, including API recall, quality recall, and quality preciSioIn