Exploring Data Mining Techniques

What is the main goal of association rule mining in data mining?

• To predict future trends

• To find interesting relationships between variables in large databases

• To classify data into predefined categories

• To reduce the dimensionality of data

Which of the following is a key measure used in association rule mining to evaluate the strength of a rule?

• Accuracy

• Confidence

• Precision

• Recall

In the context of frequent pattern growth, what does the term "frequent itemset" refer to?

• A set of items that appear together in a transaction less frequently than a given threshold

• A set of items that appear together in a transaction more frequently than a given threshold

• A single item that appears most frequently in all transactions

• A set of items that never appear together in any transaction

What is the primary advantage of the FP-Growth algorithm over the Apriori algorithm?

• It requires more memory

• It generates candidate itemsets

• It avoids the generation of candidate itemsets

• It is slower in execution

In the Apriori algorithm, what is the purpose of the "Apriori property"?

• To ensure that all itemsets are considered

• To reduce the number of candidate itemsets

• To increase the number of candidate itemsets

• To sort itemsets in descending order

Which of the following is a step in the Apriori algorithm?

• Constructing a decision tree

• Calculating the Euclidean distance

• Pruning infrequent itemsets

• Normalising data

What does the "support" measure indicate in association rule mining?

• The likelihood of a rule being incorrect

• The frequency of occurrence of an itemset in the dataset

• The accuracy of a classification model

• The number of rules generated

In frequent pattern growth, what is the purpose of the FP-tree?

• To store all possible itemsets

• To store only frequent itemsets in a compact form

• To store infrequent itemsets

• To store the entire dataset

Which of the following is a limitation of the Apriori algorithm?

• It is too fast for small datasets

• It requires a large amount of memory

• It does not generate any rules

• It cannot handle categorical data

What is the "lift" measure used for in association rule mining?

• To measure the increase in the probability of the consequent given the antecedent

• To measure the decrease in the probability of the consequent given the antecedent

• To measure the accuracy of a rule

• To measure the speed of the algorithm