MACHINE LEARNING

What is the main goal of associative rule learning in machine learning?

• Predicting numerical values

• Finding relationships between items in a dataset

• Classifying data into categories

• Reducing dataset size

Which algorithm is most commonly used for associative rule learning?

• Decision Tree

• K-Means Clustering

• Apriori

• Naïve Bayes

In association rule mining, what does "Support" measure?

• The probability that items A and B appear together

• The likelihood that B appears when A is present

• The strength of the relationship between A and B

• The number of transactions in the dataset

Which of the following statements about the ECLAT algorithm is true?

• It uses breadth-first search like Apriori

• It generates association rules directly

• It finds frequent itemsets using a depth-first search

• It does not require a minimum support threshold

What is "Lift" in associative rule learning?

• The percentage of transactions containing an itemset

• The increase in likelihood of B occurring when A is present compared to random chance

• The percentage of transactions that contain both A and B

• The total number of rules generated

Which of the following is NOT a real-world application of associative rule learning?

• Recommending products in e-commerce

• Detecting fraudulent transactions in banking

• Predicting stock prices using time series analysis

• Identifying disease patterns in healthcare

Which factor increases the computational complexity of Apriori?

• Using fewer transactions

• Setting a high minimum support threshold

• Generating a large number of candidate itemsets

• Reducing the number of items in each transaction

What is the main advantage of using FP-Growth over Apriori?

• It does not require association rule mining

• It does not scan the database multiple times

• It works only with binary data

• It does not require support thresholds

Which measure helps determine if an association rule is useful and interesting?

• Accuracy

• Precision

• Confidence

• Recall

If the Lift value of a rule is less than 1, what does it mean?

• The rule has no correlation

• The items are negatively correlated

• The items are strongly associated

• The rule has high confidence