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Data Mining MCQs - Unit-1
1. What does the acronym KDD stand for in the field of data mining?
A . Knowledge Discovery Database
B . Knowledge Database Discovery
C . Knowledge Data Definition
D . None of the above
2. Identify an option among the following which is not involved in data preprocessing.
A . Data Cleaning
B . Data Integration
C . Data Exploration
D . Data Transformation
3. Which of the following is not a data mining function?
A . Classification
B . Clustering
C . Outlier Analysis
D . Linear Programming
4. A smaller version of a data warehouse, focused on a department, is called
A . Data Mart
B . Data Cube
C . Transactional DB
D . Metadata
5. Transactional data usually includes
A . Coordinates
B . Multimedia
C . Timestamps and transaction IDs
D . Concept hierarchies
6. Identify an option among the following which is not classified based on the type of knowledge mined.
A . Classification
B . Machine Learning
C . Association
D . Clustering
7. What is the use of data cleaning?
A . to remove the noisy data
B . correct the inconsistencies in data
C . transformations to correct the wrong data.
D . All of the above
8. Data Mining is also referred to as
A . Knowledge Discovery
B . Data Integration
C . Data Transformation
D . Data Selection
9. ___________________ the process of converting raw data into a format that is suitable for mining.
A . Data Cleaning
B . Data Integration
C . Data Reduction
D . Data Transformation
10. In which step of Knowledge Discovery, multiple data sources are combined?
A . Data Cleaning
B . Data Integration
C . Data Selection
D . Data Transformation
11. In Data mining architecture, the core component is
A . Knowledge Base
B . Data Mining Engine
C . Database
D . Pattern Evaluation Module
12. __________ may be defined as the data objects that do not comply with the general behavior or model of the data available.
A . Outlier Analysis
B . Evolution Analysis
C . Prediction
D . Classification
13. Which mining functionality focuses on future prediction?
A . Descriptive mining
B . Predictive mining
C . Association mining
D . Outlier mining
14. Which of the following is not a data mining task?
A . Classification
B . Clustering
C . Regression
D . Linear Programming
15. Which method can be used for smoothing noisy data?
A . Binning
B . Regression
C . Clustering
D . All of the above
16. Which of the following is not a type of data preprocessing technique?
A . Sampling
B . Normalization
C . Standardization
D . Principal component analysis
17. Which of the following is NOT a data mining application?
A . Retail
B . Banking
C . Healthcare
D . Data Backup
Fill in the Blanks
18. Classification is a _______ learning technique, while clustering is _______ learning.
19.________________ is a process of finding potentially useful patterns and valuable information from huge amount of data.
20. __________________ is defined as the process where data relevant to the analysis is decided and retrieved from the data collection.
21. ______________________ is a data mining technique used to categorize the items into predefined classes or labels based on some predefined properties.
22. _______________________ module evaluates the discovered patterns to determine their usefulness and relevance.
23._______________________is defined as the process of transforming data into appropriate form required by mining procedure.
24. Removing duplicate records is a process called ___________________________
25. _______________________ evaluate the discovered patterns to determine their usefulness and relevance.
26. ____________________is an essential process where intelligent methods are applied to extract useful patterns/knowledge.
27. The data needs to be _____________________,__________________ and ________________ before passing it to the database or data warehouse server.
28. The KDD process step that removes irrelevant and noisy data is __________________.
29. When data that cannot be grouped in any of the class appears. That type of data is called as _____________________
30. A data warehouse is usually modelled by a multidimensional data structure, called a __________________________
31. Data on spatial databases are stored as ________________,____________________,__________________ and ________________.
32. _________________ aims to reduce dataset size while preserving important information.
33. In __________________ the Data Mining system will not utilize any function of data warehouse system or database.
34. Classification uses methods like ___________________,__________________ or _____________________ to predict a class or essentially classify a collection of items.
35. The sequence of data point collected over time intervals is called as _________________.
36. ______________________ is one of the data mining functionalities that help the analyst find the missing numeric values.
Relevant Materials :
☞ Data Mining MCQs - Unit-1 - [ DM ]
☞ Data Mining MCQs - Unit-2 - [ DM ]
☞ Data Mining MCQs - Unit-3 - [ DM ]
☞ Data Mining MCQs - Unit-4 - [ DM ]
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