Question

Define each of the following data mining functionalities: characterization, discrimination, association and correlation analysis, classification, prediction, clustering,
and evolution analysis.Give examples of each data mining functionality,using a real-life database with which you are familiar.

Answer 1

Explanation:

Data Mining Functionalities

Data mining functionalities are used to specify the kind of patterns to be found in data mining tasks.Data mining tasks can be classified into two categories: descriptive and predictive.

Descriptive mining tasks characterize the general properties of the data in the database.

Predictive mining tasks perform inference on the current data in order to make predictions.

Answer 2

Explanation:

Characterization: Data characterization is a summarization of the general characteristics or features of a target class of data.

For example- the characteristics of students can be produced, generating a profile of all the University first year computer science students, which may include such information as a high GPA and large number of courses taken.

Discrimination: Data discrimination is a comparison of the general features of target class data objects with the general features of objects from one or a set of contrasting classes.

For example- the general features of students with high GPA's may be compared with the general features of students with low GPA's. The resulting description could be a general comparative profile of the students such as 75% of the students with high GPA's are fourth -year computer science students