Data Mining And Knowledge Discovery
Market Basket Analysis and Predictive Modelling
- 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
Back to top