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Data Mining: Chapter 2 Lecture Notes Quiz

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Data Mining: Chapter 2 Lecture Notes Quiz

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Questions and Answers

What is another term for an attribute in Data Mining and Machine Learning?

Coefficient

Variable (correct)

Constant

Parameter

In the given data set, which attribute is an example of a nominal type?

Marital Status (correct)

Cheat

Refund

Taxable Income

What distinguishes attribute values from attributes?

Attribute values are numbers or symbols assigned to an attribute, while attributes are properties or characteristics of an object. (correct)

Attribute values are properties or characteristics of an object, while attributes are numbers or symbols assigned to an object.

Attribute values represent the type of attribute, while attributes represent the specific value assigned to an object.

Attributes represent the type of attribute, while attribute values represent the specific value assigned to an object.

Which type of attribute includes examples like ID numbers and eye color?

<p>Nominal</p> Signup and view all the answers

What is another term for an object in Data Mining and Machine Learning?

<p>Record</p> Signup and view all the answers

Study Notes

Data Mining and Machine Learning Terminology

An attribute is also referred to as a feature or variable in Data Mining and Machine Learning.
In a given data set, an attribute that is an example of a nominal type is one that has no inherent order or ranking, such as marital status or occupation.

Attributes and Attribute Values

Attribute values are the specific instances of an attribute, whereas the attribute itself is the characteristic or property being measured.
For example, "eye color" is an attribute, while "blue" and "brown" are its attribute values.

Nominal Attributes

Nominal attributes include examples like ID numbers and eye color, which are categorical and have no inherent order or ranking.

Objects in Data Mining and Machine Learning

An object is also referred to as a record, tuple, or data point in Data Mining and Machine Learning, and it represents a single instance or observation.

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Description

Test your knowledge of data mining concepts covered in Chapter 2 lecture notes by Tan, Steinbach, and Kumar, adapted by Michael Hahsler. The quiz includes topics such as attributes/features, types of data sets, data quality, data preprocessing, similarity and dissimilarity, and density.