Question

List and describe five primitives for specifying data mining task.

Answer 1

Following are the five primitives for specifying data mining task:

1. Task-relevant data: This specifies the quantities of the database or the set of records wherein the user is interested. This includes the database attributes or records warehouse dimensions of interest.
2. The kind of knowledge to be mined: This specifies the data mining capabilities or functions to be performed, along with characterization, discrimination, affiliation or correlation analysis, classification, prediction, clustering, outlier analysis, or evolution analysis.
3. Background knowledge (concept hierarchies): This expertise about the domain to be mined is beneficial for steering the information discovery process and for comparing the styles found. Concept hierarchies are a popular shape of back- ground understanding, which allow records to be mined at more than one stages of abstraction .
4. Interestingness measures: This might be used to guide the mining process or, after discovery, to evaluate the discovered patterns. Different kinds of information or knowledge may have different interestingness measures.
5. Representation for visualizing the discovered patterns:  This specifies the form in which patterns that are discovered are to be displayed, which may include rules, tables, charts, graphs, decision trees, and cubes.

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Answer 2

Answer:

Explanation:

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