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 reallife database that you are familiar with.

Answer 1

Answer:

In the clarification portion below, the definition according to the received information is summarized.

Explanation:

• Characterization:

It is indeed a summary of general object characteristics in something like a target class and creates characteristic laws.

• Discrimination:

Just before predefined data types have been held to a different standard from everyone else, it's indeed bias which always happens.

• Association:

It's a mechanism that determines the possibility that objects in a set will co-occur.

• Classification:

It is indeed duction which attributes elements to target groups or classes in a set.

• Prediction:

It is solely dependent on either the interpretation of other similar values to classify data points.

• Clustering:

It has been used to position the components of the information through their corresponding classes.

• Evolution Analysis:

It would be for objects whose behavior varies throughout time to explain or design regularities.