DMW1

Training set is needed for:

• Association rule discovery

• Clustering

• Classification

Data reduction is perform at:

• Data collection

• Pattern extraction and discovery

• Data preprocessing

The number of Data Mining steps is:

• 4

• 5

• 6

Association rule discovery is of type:

• Description

• Prediction

• Prescription

Regression is of type:

• Description

• Prediction

• Prescription

Clustering is of type:

• Prediction

• Prescription

• Description

A nearest neighbor approach is best used

• with large-sized datasets

• when irrelevant attributes have been removed from the data

• when a generalized model of the data is desireable

• when an explanation of what has been found is of primary importance

Which statement about outliers is true?

• Outliers should be identified and removed from a dataset

• Outliers should be part of the training dataset but should not be present in the test

  data

• Outliers should be part of the test dataset but should not be present in the training

  data

• The nature of the problem determines how outliers are used

Assume that we have a dataset containing information about 200 individuals. One

hundred of these individuals have purchased life insurance. A supervised data mining

session has discovered the following rule

• 63

• 70

• 30

• 27

Unlike traditional production rules, association rules

• allow the same variable to be an input attribute in one rule and an output attribute in

  another rule

• allow more than one input attribute in a single rule

• require input attributes to take on numeric values

• require each rule to have exactly one categorical output attribute