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Association Analytics  – Association Rule  Mining

Quiz by Muhammad Afif

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15 questions
Show answers
  • Q1
    Association analytics, also known as association rule mining, is a technique used to:
    Calculate summary statistics
    Predict future market trends
    Classify data into categories
    Discover interesting relationships or patterns in large datasets
    30s
  • Q2
    Association rule mining is a data mining technique that aims to find:
    Frequent patterns or associations among items in a dataset
    Optimal clustering solutions
    Outliers in a dataset
    Accurate regression models
    30s
  • Q3
    What is the purpose of support in association rule mining?
    To measure the significance of a rule in a dataset
    To measure the confidence of a rule in a dataset
    To measure the frequency of a rule in a dataset
    To measure the lift of a rule in a dataset
    30s
  • Q4
    In association rule mining, what is confidence?
    A measure of the frequency of a rule
    A measure of the lift of a rule
    A measure of the reliability of a rule
    A measure of the significance of a rule
    30s
  • Q5
    What is the lift measure in association rule mining?
    A measure of the probability of the consequent given the antecedent
    A measure of the frequency of a rule in a dataset
    A measure of the reliability of a rule
    A measure of how much better a rule predicts an outcome compared to random chance
    30s
  • Q6
    What is the Apriori algorithm in association rule mining?
    An algorithm used to calculate summary statistics
    An algorithm used to classify data into categories
    An algorithm used to perform clustering analysis
    An algorithm used to generate frequent itemsets from a transaction dataset
    30s
  • Q7
    What is the purpose of the lift measure in association rule mining?
    To measure the strength of association between items in a rule
    To measure the frequency of a rule in a dataset
    To measure the confidence of a rule in a dataset
    To measure the reliability of a rule
    45s
  • Q8
    Which of the following is an application of association rule mining in e-commerce?
    Image recognition
    Network intrusion detection
    Sentiment analysis
    Market basket analysis
    30s
  • Q9
    What is a limitation of the Apriori algorithm?
    It cannot handle continuous attributes
    It has a slow execution time
    It requires a large amount of memory
    It is not suitable for large datasets
    30s
  • Q10
    What is an advantage of the Apriori algorithm?
    It is not suitable for large datasets
    It cannot handle continuous attributes
    It requires a large amount of memory
    It is easy to understand and implement
    30s
  • Q11
    What is a disadvantage of the Apriori algorithm?
    It is not suitable for large datasets
    It requires a large amount of memory
    It cannot handle continuous attributes
    It is easy to understand and implement
    30s
  • Q12
    In a sample of 300 college students (18-21 years old), 200 students watch sports TV shows, 60 students watch scientific TV shows, and 20 students watch both sports and scientific TV shows. What is the support, confidence and lift of students watching scientific TV shows given they watch sports TV shows?
    Support: 0.0667, Confidence: 0.2, Lift: 0.7
    Support: 0.5, Confidence: 0.2, Lift: 0.6
    Support: 0.0667, Confidence: 0.1, Lift: 0.5
    Support: 0.2, Confidence: 0.3, Lift: 0.5
    300s
  • Q13
    You are a financial analyst at a company which executed 500 transactions last year. Out of these, 120 transactions involved both equities and derivatives. If there were 200 transactions involving equities, calculate the support, confidence, and lift for the rule 'if equities then derivatives'.
    Support: 0.6, Confidence: 0.24, Lift: 2
    Support: 0.24, Confidence: 0.6, Lift: 2.5
    Support: 0.2, Confidence: 0.48, Lift: 2.4
    Support: 0.3, Confidence: 0.5, Lift: 1.67
    300s
  • Q14
    If the support is 0.70, confidence is 0.30 and lift is 1.3 in studies involving college students aged 18-21, which metric needs to be improved?
    All are already at optimal levels
    Confidence
    Lift
    Support
    120s
  • Q15
    What action should be taken if the support of associating items in a supermarket for marketing promotions is 0.45, confidence is 0.60, and lift is 0.95?
    Promote the associated items separately in marketing campaigns targeting general population.
    Promote the associated items together in marketing campaigns targeting college students.
    Promote the associated items separately in marketing campaigns targeting the college students.
    Promote the associated items together in marketing campaigns targeting the general population.
    120s

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