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.

Respuesta :

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.