Explore key concepts in Data Mining and Knowledge Discovery with questions on data partitioning, CRISP DM phases, SAS Enterprise Miner, and more. This quiz assesses skills in predictive modeling and market basket analysis, vital for professionals in data-driven roles.
Low support and confidence.
Low support but high confidence and great lift
High support and confidence as well as great lift.
None of the above
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Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, Deployment
Data Understanding, Data Preparation, Business Understanding, Modeling, Evaluation, Deployment
Data Understanding, Business Understanding, Data Preparation, Modeling, Evaluation, Deployment
Business Understanding, Data Preparation, Data Understanding, Modeling, Evaluation, Deployment
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Data Understanding
Data Partitioning
Association Analysis
Predictive Modeling
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ONLY for Market Basket Analysis
ONLY for Predictive Modeling
Creating Accurate Descriptive and Predictive Models
None of the above
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The process of using decision trees to predict certain outcomes.
Is the process of developing clusters in order to segregate data and discover the relevant categories of data.
The process of discovering association rules between variables in a dataset.
None of the above.
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The general measure of association between the two item sets.
The conditional probability that a transaction contains item set B given that it contains item set A
The probability that the two item sets occur together.
The conditional probability that a transaction contains item set B given that it does not contain item set A.
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The process of discovering association rules between variables in a dataset.
Is the process of developing clusters in order to segregate data and discover the relevant categories of data.
Market Basket analysis uses decision trees to predict outcomes.
All of the above.
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True
False
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Collecting relevant data.
Finding and identifying any problems within the data sets.
Cleaning and addressing any problems with the data sets.
These are all part of the data understanding phase
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The overall method of creating models to address real world situations
The method of understanding and identifying the outcome of the data
The method of developing steps and/or methods in order to clarify the data.
None of the above
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