
MTS 488 lesson 4
Authored by Jantakarn Wannasuk
Computers
University
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8 questions
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1.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
Why do we need data preprocessing?
To make data more challenge to analyze
To increase the amount of data available for analysis
To increase the chances of overfitting the model.
2.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
What does the phrase "Garbage in, Garbage out" refer to in the context of data preprocessing?
The idea that the quality of output data is dependent on the quality of input data.
3.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
Which of the following is NOT listed as a common type of dirty data?
Misfielded values
Consistent data
Attribute dependencies
4.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
What is the primary purpose of regression in handling noisy data?
To smooth the data by fitting it to a function.
To detect outliers
To predict missing values
5.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
What is a better way to handle missing values in a dataset?
Replace missing values with the mean of the same attribute.
Ignoring the tuple entirely.
6.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
How is the "entity identification problem" typically solved in data integration?
By removing all metadata from databases.
By using a unified schema for all databases.
By ignoring the problem as it rarely occurs.
By relying on metadata as a reference.
7.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
What does "min-max normalization" involve in data transformation?
Converting categorical data into boolean values.
Scaling data to fall within a specified range.
Summarizing data by removing noise.
Transforming data to a logarithmic scale
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