[amp_mcq option1=”selective data mining” option2=”query-driven data mining” option3=”model-driven data mining” option4=”rule-based data mining” correct=”option1″]
The correct answer is A. selective data mining.
Data mining is the process of extracting patterns from data. It is a subset of knowledge discovery in databases (KDD). Data mining is used in a wide variety of fields, including business, science, and medicine.
There are many different types of data mining, including:
- Query-driven data mining: This type of data mining is driven by a specific question or query. The goal is to find patterns in the data that answer the question.
- Model-driven data mining: This type of data mining is driven by a specific model. The goal is to find patterns in the data that fit the model.
- Rule-based data mining: This type of data mining is driven by a set of rules. The goal is to find patterns in the data that follow the rules.
- Descriptive data mining: This type of data mining is used to describe the data. The goal is to find patterns in the data that describe the data.
- Predictive data mining: This type of data mining is used to predict future events. The goal is to find patterns in the data that can be used to predict future events.
- Prescriptive data mining: This type of data mining is used to make recommendations. The goal is to find patterns in the data that can be used to make recommendations.
Selective data mining is not a type of data mining. It is a process of selecting data from a database for further analysis.