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BSCS 4-2 - CS Elective 4 (Data Mining)

Total questions: 20

Worksheet time: 10mins

Name
Class
Date
1.

Which of the following stages of data mining processes that we unify and convert data within formats from the source system up to the required destination system

a)

Data Integration

b)

Data Cleaning

c)

Data Transformation

d)

Data Selection

2.

Identifying data points purely on the description of another related data value to determine how they act in an upcoming time

a)

Identification

b)

Prediction

c)

Optimization

d)

Classification

3.

Which of the following is the correct statement about data mining?

a)

A subject-oriented integrated time variant non-volatile collection of data support of management

b)

The actual discovery phase of a knowledge discovery processes

c)

The stage of selecting the right data for Knowledge Discovery in Databases (KDD) process.

d)

Group of similar objects that differ significantly from other objects.

4.

Which of the following scenario is example of data mining?

a)

Agencies can find out which area is more prone to crime and how much police personnel should be deployed

b)

To find out the yield of vegetables with the amount of water required by the plants

c)

Finding factors that influence the customer’s decisions towards banking

d)

All of the mentioned

5.

A process of making a group of different data objects into classes of similar data objects

a)

Classification

b)

Regression

c)

Clustering

d)

Association

6.

One of the data mining issues which deals in expressing the discovered knowledge in different expressive forms so that it can be easily understood

a)

Incorporation of Background Knowledge

b)

Pattern Evaluation.

c)

Efficiency and Scalability of Data Mining Algorithms.

d)

Presentation and Visualization of Data Mining Results

7.

A stage in Data Ming Processes where we obtain only relevant data for analysis from the collection of data.

a)

Data Cleaning

b)

Data Integration

c)

Data Transformation

d)

Data Selection

8.

One of the activities performed in data mining is summarization, which means?

a)

To find out the group of objects which are similar to each other but are different from the object in another group

b)

To find out the overall generated data and its calculation in an easily comprehensible and informative manner

c)

To find out the continuous quantity for new observations using the knowledge gained from the previous data

d)

To accurately find out the target class for each case in the data

9.

One of the major issues in data mining that deals with how efficient the data mining algorithm is, to effectively extract information from huge amount of data in many data repositories

a)

Performance Issue

b)

Diverse Data types Issue

c)

User Interface Issue

d)

Mining Methodology Issue

10.

Which of the following is NOT a data mining technique?

a)

Regression analysis

b)

Clustering

c)

Random sampling

d)

Decision trees

11.

What are the sub-stages included in data preparation?

a)

Cleaning, Integration, Selection, Transformation

b)

Cleaning, Integration, Selection, Data Mining

c)

Cleaning, Selection, Integration, Evaluation

d)

Cleaning, Transformation, Evaluation, Data Mining

12.

One of the data mining issues that deals with uncertain data which sometimes lead to wrong or incorrect pattern

a)

Handling Noisy or Incomplete Data

b)

Pattern Evaluation

c)

Mining Information from Heterogeneous Databases and Global Information

d)

Handling Relational and Complex Types of Data

13.

Which of the following is a major issue in data mining related to data quality?

a)

Bias in the data

b)

Lack of transparency in models

c)

Handling large datasets

d)

Lack of interpretability

14.

Which of the following is a major issue in data mining related to scalability?

a)

Bias in the data

b)

Lack of transparency in models

c)

Handling large datasets

d)

Lack of interpretability

15.

What might be the impact of outliers on data mining algorithms?

a)

Outliers can cause data mining algorithms to perform poorly

b)

Outliers do not have any impact on data mining algorithms

c)

Outliers can improve the performance of data mining algorithms

d)

Outliers can only impact certain types of data mining algorithms

16.

Which of the following techniques can be used to detect outliers?

a)

Clustering

b)

Regression analysis

c)

Boxplots

d)

All of the above

17.

Which of the following is an example of a data mining user interface issue?

a)

Developing new algorithms for analyzing the data

b)

Providing support for multiple data sources

c)

Improving the performance of existing algorithms

d)

All of the above

18.

A company is using a data mining algorithm to analyze their customer data in real-time. However, the algorithm is taking too long to generate results. Which technique can be used to improve the performance of the algorithm?

a)

Sampling

b)

Parallel processing

c)

Data cleaning

d)

Data transformation

19.

A data mining algorithm is generating inaccurate results due to noise and outliers in the dataset. Which technique can be used to improve the accuracy and performance of the algorithm?

a)

Sampling

b)

Parallel processing

c)

Data cleaning

d)

Data transformation

20.

A company is using data mining techniques to analyze their sales data and predict future sales trends. They use the data mining results to make strategic decisions. This is an example of descriptive data mining

a)

True

b)

False