Data Mining And Knowledge Discovery

11 Questions | Total Attempts: 723

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Data Mining Quizzes & Trivia

Market Basket Analysis and Predictive Modelling


Questions and Answers
  • 1. 
    Dividing a database into 3 parts; a training data set, validation data set and testing data set is known as:
    • A. 

      Data Understanding

    • B. 

      Data Partitioning

    • C. 

      Association Analysis

    • D. 

      Predictive Modeling

  • 2. 
    What is the correct order for the 6 CRISP DM phases?
    • A. 

      Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, Deployment

    • B. 

      Data Understanding, Data Preparation, Business Understanding, Modeling, Evaluation, Deployment

    • C. 

      Data Understanding, Business Understanding, Data Preparation, Modeling, Evaluation, Deployment

    • D. 

      Business Understanding, Data Preparation, Data Understanding, Modeling, Evaluation, Deployment

  • 3. 
    What is SAS Enterprise Miner used for:
    • A. 

      ONLY for Market Basket Analysis

    • B. 

      ONLY for Predictive Modeling

    • C. 

      Creating Accurate Descriptive and Predictive Models

    • D. 

      None of the above

  • 4. 
    What is Market Basket Analysis?
    • A. 

      The process of discovering association rules between variables in a dataset.

    • B. 

      Is the process of developing clusters in order to segregate data and discover the relevant categories of data.

    • C. 

      Market Basket analysis uses decision trees to predict outcomes.

    • D. 

      All of the above.

  • 5. 
    What is Predictive Modeling?
    • A. 

      The process of using decision trees to predict certain outcomes.

    • B. 

      Is the process of developing clusters in order to segregate data and discover the relevant categories of data.

    • C. 

      The process of discovering association rules between variables in a dataset.

    • D. 

      None of the above.

  • 6. 
    What is Data Processing and Analysis?
    • A. 

      The overall method of creating models to address real world situations

    • B. 

      The method of understanding and identifying the outcome of the data

    • C. 

      The method of developing steps and/or methods in order to clarify the data.

    • D. 

      None of the above

  • 7. 
    Association rules describe the relationships between certain variables in a large database.
    • A. 

      True

    • B. 

      False

  • 8. 
    In market basket analysis; confidence is:
    • A. 

      The general measure of association between the two item sets.

    • B. 

      The conditional probability that a transaction contains item set B given that it contains item set A

    • C. 

      The probability that the two item sets occur together.

    • D. 

      The conditional probability that a transaction contains item set B given that it does not contain item set A.

  • 9. 
    In market basket analysis; support is: The general measure of association between the two item sets.
    • A. 

      True

    • B. 

      False

  • 10. 
    Which of these is NOT part of the CRISP DM Data Understanding phase?
    • A. 

      Collecting relevant data.

    • B. 

      Finding and identifying any problems within the data sets.

    • C. 

      Cleaning and addressing any problems with the data sets.

    • D. 

      These are all part of the data understanding phase

  • 11. 
    When discovering association rules; it is most important to look for rules that generate: 
    • A. 

      Low support and confidence.

    • B. 

      Low support but high confidence and great lift

    • C. 

      High support and confidence as well as great lift.

    • D. 

      None of the above

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