Please answer the three Qs. Thank You

Which statements are correct about patterns and pattern mining? Pattern mining is to find similar items in a data set. Patterns are a set of items, subsequences, or substructures that occur frequently together (or strongly correlated) in a data set Patterns represent intrinsic and important properties of datasets. Pattern mining is to uncover itemsets, subsequences, or substructures that appear frequently in a data set. Finding frequent patterns plays an essential role in mining associations, correlations, and many other interesting relationships among data. Patterns can be represented in the form of association rules. For example, AB,C[support=d%,confidence=e%] means the association rule A=>B,C with a support of d% and a confidence of e%. Rule support and confidence are two measures of rule interestingness. Support reflects the usefulness of this discovered rule. Confidence reflects the certainty of discovered rule. Support is calculated as a percentage of cases that A, B, C appear together in the task-relevant data. Confidence is calculated as a percentage of cases that B and C appear in the task-relevant data of containing A. Given the following data set, what is the support of the association rule Milk ->Bread? Note that TID is the transaction ID. \begin{tabular}{l} 60% \\ \hline 20% \\ \hline 40% \\ \hline 80% \end{tabular} Given the following data set, what is the confidence of the association rule Milk > Bread? Note that TID is the transaction ID. \begin{tabular}{l} 85% \\ 95% \\ 40% \\ 80% \\ \hline 60% \\ 75% \end{tabular}