Data Warehousing and Data Mining · Unit 2 · 2 hrs
Introduction to Data Mining
Exam-focused notes for Introduction to Data Mining (Data Warehousing and Data Mining, CSC420): what the TU syllabus asks and how it has actually been tested, with 7 solved past questions from this unit.
What this unit covers
- Motivation for data mining
- Introduction to data mining system
- Data mining functionalities
- KDD
- Data object and attribute types
- Statistical description of data
- Issues and Applications
KDD
How KDD differs from data mining? Explain various stages of KDD with suitable block diagram. [5]
KDD (Knowledge Discovery from Data) is the overall process of discovering useful knowledge from raw data. It is a complete, iterative, multi-step process. Data Mining is just one step within the larger KDD process, where intelligent methods (algorithms) are...
Full solved answer →Differentiate between KDD and data mining. [5]
KDD (Knowledge Discovery from Databases) is the overall process of discovering useful, valid, and understandable knowledge from large amounts of data. It is a complete, iterative, and interactive process. Data Mining is a single step within the KDD process ...
Full solved answer →How does KDD differ with data mining? Describe the stages of data mining. [5]
KDD (Knowledge Discovery from Data) is the overall process of discovering useful knowledge from raw data. Data Mining is just one step within this larger KDD process. Aspect KDD Data Mining --------- Scope Entire process from raw data to knowledge A single ...
Full solved answer →Data object and attribute types
Discuss different types of attributes with suitable example of each. [5]
An attribute (also called a feature or variable) is a data field representing a characteristic or feature of a data object. Attributes can be of different types depending on the nature of their values. --- A nominal attribute has values that are names or la...
Full solved answer →Issues and Applications
When a pattern is said to be interesting? List the issues of data mining. [5]
A pattern is said to be interesting if it is: 1. Easily understood by humans 2. Valid on new or test data with some degree of certainty 3. Novel (previously unknown or validates a hypothesis) 4. Useful (can be acted upon to gain some advantage) 5. Non-trivi...
Full solved answer →Are the information given by data mining is always useful? What are the issues in data warehousing and data mining? [5]
No, the information given by data mining is not always useful. Data mining may produce patterns or results that are: - Trivial - already known to domain experts and provide no new insight - Irrelevant - not applicable to the business problem at hand - Misle...
Full solved answer →Motivation for data mining
Give a syntax and example of data mining query language. [5]
A data mining query is a structured specification that allows users to interactively communicate with the data mining system to direct the mining process. Data mining tasks can be specified in the form of a data mining query, which is defined in terms of da...
Full solved answer →Make Unit 2 stick
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