0
Multilevel and Multidimensional Association rules?

Mumbai University > Information Technology > Sem6 > Data Mining and Business Intelligence

Marks: May 2015

Year: 10M

0  upvotes
0

Multilevel Mining Association Rules:

  • Items often form hierarchy.
  • Items of the lower level are expected to have lower support.
  • A common form of background knowledge as that an attribute may be generated or specialized according to a hierarchy of concepts.
  • Rules which contain associations with hierarchy of concepts are called Multilevel Association Rules.

enter image description here

Fig: Hierarchy of concept

Support and confidence of Multilevel association rules:

  • Generalizing / specializing values of attributes affects support and confidence.
  • Support of rules increases from specialized to general.
  • Support of rules decreases from general to specialized.
  • Confidence is not affected for general or specialized.

Multidimensional Mining (MD) Association Rules:

  • Single – dimension rules: It contains the single distinct predicate i.e. buys Buys(X, “milk”) = buys (X,”bread”)
  • Multi-dimensional rule: It contains more than one predicate
  • Inter-dimension association rule: It has no repeated predicate
  • Age (X,”19-25”) ^ occupation (X, “student”) = buys (X, “coke”).
  • Hybrid dimension association rules: It contains multiple occurrence of the same predicate i.e. buys Age(X, “19-25”) ^ buys (X, “popcorn”) = buys (X, “coke”)
  • Categorical Attributes: This have finite number of possible values, no ordering among values. Example; brand, color.
  • Quantitative Attributes: these are numeric and implicit ordering among values Example; age, income.
0  upvotes
Please log in to add an answer.

Next up

Read More Questions

If you are looking for answer to specific questions, you can search them here. We'll find the best answer for you.

Search

Study Full Subject

If you are looking for good study material, you can checkout our subjects. Hundreds of important topics are covered in them.

Know More