Data Mining Chapter 2

Generate an educational illustration depicting concepts of data mining, including visual elements like graphs, data points, and statistical symbols, emphasizing analysis and understanding of data.

Data Mining Quiz: Test Your Knowledge

Welcome to the Data Mining Quiz! This engaging quiz consists of 28 questions designed to challenge your understanding of essential concepts in data mining. Whether you're a student, teacher, or data enthusiast, this quiz offers a great opportunity to assess your knowledge and learn more about the subject.

Key features of the quiz include:

Multiple choice questions
Instant feedback on your answers
Variety of topics including statistics, data visualization, and distance measures

28 Questions7 MinutesCreated by AnalyzingTree421

�…. Is a data field, representing a characteristic or feature of a data object.

Attribute

Dimension

Fact

A and B

All of the following are attribute types except:

Descriptive

Nominal

Numeric

Binary

Given two objects represented by tuples (3, 5) and (2, 0). What is the Euclidean distance between two objects?

5.1

None

Given two objects represented by tuples (3, 5) and (2, 0). What is the Manhattan distance between two objects?

5.1

None

Euclidean distance is also known as ______________

L-1 norm

L-2 norm

L-3 norm

None

�.. Attribute has only a finite or countably infinite set of values while …. Attribute has real numbers as attribute values.

Discrete, continuous

Continuous, discrete

Qualitative, quantitative

Quantitative, qualitative

Value that occurs most frequently in the data?

Mean

Mode

Median

None

Middle value if odd number of values, or average of the middle two values otherwise.

Mean

Median

Mode

None

At symmetric data distribution

Mean = Mode

Mode = Median

None

A and B

The following graph represents …… data.

Positively correlated data

Uncorrelated data

Negatively correlated data

All of the above

All of the following measure data dispersion except:

Variance

Inter-Quartile range

Standard deviation

Mode

Basic statistical descriptions can be displayed graphically by:

Boxplot

Histogram

Scatter plot

All of the above

�… Graph display of tabulated frequencies, shown as bars

Boxplot

Histogram

Scatter plot

All of the above

�… is a numerical measure of how alike two data objects are.

Similarity

Proximity

Dissimilarity

All of the above

Is a numerical measure of how different two data objects are.

Similarity

Proximity

Dissimilarity

All of the above

We use data visualization to ….

To Gain insight into an information space

Search for patterns

Provide qualitative overview of large data sets

All of the above

In Pixel-Oriented Visualization Techniques for a data set of M dimensions we create ….. Windows on the screen.

M+1

2^M

M–1

Data set has more than mode

Unimodal

Bimodal

Trimodal

All of the above

Data objects are described by attributes.

True

False

Data objects are made up of data sets.

True

False

Dissimilarity value is lower when objects are more alike

True

False

Manhattan distance is represented by a direct line.

True

False

Similarity value is lower when objects are more alike.

True

False

We can achieve the Pixel-Oriented Visualization Techniques using direct visualization.

True

False

Scatterplot is one of the ways to achieve Geometric Projection Visualization Techniques.

True

False

In Pixel-Oriented Visualization Techniques the colors of the pixels reflect the corresponding dimensions.

True

False

We use data visualization because it helps find interesting regions and suitable parameters for further quantitative analysis

True

False

In Parallel Coordinates the axes are equidistant.

True

False

Data Mining Chapter 2

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