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Data Mining MCQs - Unit-1
1. What is true about data mining?
A . Data Mining is defined as the procedure of extracting information from huge sets of data
B . Data mining also involves other processes such as Data Cleaning, Data Integration, Data Transformation
C . Data mining is the procedure of mining knowledge from data.
D . All of the above
2. 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
3. "Efficiency and scalability of data mining algorithms" issues comes under?
A . Mining Methodology and User Interaction Issues
B . Performance Issues
C . Diverse Data Types Issues
D . None of the above
4. 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
5. Choose the options below that a data warehouse can include.
A . Flat files
B . Online data
C . Database tables
D . All the above
6. "Handling of relational and complex types of data" issue comes under?
A . Mining Methodology and User Interaction Issues
B . Performance Issues
C . Diverse Data Types Issues
D . None of the above
7. 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
8. 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
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.) Data Mining System Classification consists of?
A . Database Technology
B . Machine Learning
C . Information Science
D . All of the above
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.) DMQL stands for?
A . Data Mining Query Language
B . Dataset Mining Query Language
C . DBMiner Query Language
D . Data Marts Query Language
14.) Which of the following is not a data mining task?
A . Classification
B . Clustering
C . Regression
D . Linear Programming
15.) What is the difference between supervised and unsupervised learning?
A . Supervised learning requires labeled data, while unsupervised learning does not.
B . Supervised learning uses clustering algorithms, while unsupervised learning uses classification algorithms.
C . Supervised learning is used for regression analysis, while unsupervised learning is used for clustering.
D . There is no difference between supervised and unsupervised learning.
16.) Which of the following is not a type of data preprocessing technique?
A . Sampling
B . Normalization
C . Standardization
D . Principal component analysis
Fill in the Blanks
17.________________ is a process of finding potentially useful patterns and valuable information from huge amount of data.
18. __________________ is defined as the process where data relevant to the analysis is decided and retrieved from the data collection.
19. ______________________ is a data mining technique used to categorize the items into predefined classes or labels based on some predefined properties.
20._______________________is defined as the process of transforming data into appropriate form required by mining procedure.
21. Removing duplicate records is a process called ___________________________
22. _______________________ evaluate the discovered patterns to determine their usefulness and relevance.
23. ____________________is an essential process where intelligent methods are applied to extract useful patterns/knowledge.
24. The data needs to be _____________________,__________________ and ________________ before passing it to the database or data warehouse server.
25. When data that cannot be grouped in any of the class appears. That type of data is called as _____________________
26. A data warehouse is usually modelled by a multidimensional data structure, called a __________________________
27. Data on spatial databases are stored as ________________,____________________,__________________ and ________________.
28. In __________________ the Data Mining system will not utilize any function of data warehouse system or database.
29. Classification uses methods like ___________________,__________________ or _____________________ to predict a class or essentially classify a collection of items.
30. ______________________ 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 ]
☞ Data Mining MCQs - Unit-5 - [ DM ]
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