G20: Data Mining

The problem of finding hidden structures in unlabeled data is called:

• Supervised learning

• Unsupervised learning

• 1. Candidate Generation

• 1. None of the above

Which of the following is not a process in data mining?

• Knowledge extraction

• Cluster analysis

• Data exploration

• Data transformation

A cluster is...

• 1. A group of similar objects that differ significantly from other objects in a different group

• Operation on a database to transform or simplify data in order to prepare it for a machine learning algorithm

• 1. Symbolic representation of facts or ideas from which information can potentially be extracted

Which of the following is an unsupervised data mining technique?

• Cluster analysis

• Feature extraction

• Frequent pattern mining

• All of the above

Which of the following methods is the recommended method for estimating accuracy of a classifier?

• Stratified 10-fold cross-validation

• Classifying holdout validation

• Random sampling classification

• Sampling accuracy validation

Which of the following central tendency measures is used in attribute selection method for defining splitting criterion for an attribute?

• Mean of the attribute

• Median of the attribute

• Mode of the attribute

• None of the above

What cross-validation technique is recommended for estimating accuracy?

• Stratified 10-fold cross-validation

• K-fold cross-validation

• 1. Leave-one-out

• Leaf node validation

The Bayesian Classifier is a probability classifier.

• True

• False

Naive Bayesian DOES NOT benefit from having strong feature independence assumptions.

• True

• False

Bayes theorem converts the results from your test into the real probability of the event.

• True

• False