This set of Data Mining Multiple Choice Questions & Answers (MCQs) focuses on “Data Objects and Attribute Types”.
1. The basic building block of a data set is _____
a) Data mining
b) Data object
c) Cluster
d) Association rules
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Explanation: A data set is a collection of data objects. A data object may represent a real-world entity, accompanied by some attributes or features which describe the properties of the data object.
2. Which part of the database corresponds to the data points stored in it?
a) Rows of a database
b) Columns of a database
c) Index of a database
d) Schema of a database
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Explanation: A data object, also known as a data point, represents a real-world entity described by some attributes. When a data object is stored in a database, referred to as a data tuple, rows of the database corresponds to the data object.
3. For a data object stored in a database, the attributes of the data object are represented by _____
a) Columns of the database
b) Rows of the database
c) Relation schema
d) Relational index
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Explanation: The data objects, when stored in a database, are also referred to as data tuples. Since a database is usually made up of rows and columns, the rows of the database represent the data object and the columns of the database represent the attributes describing the data object.
4. Which of the following does not describe the properties of a data object?
a) Attributes
b) Features
c) Dimensions
d) Instances
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Explanation: A data object, also referred by names such as example, sample, instance, represent a real-world entity. The attributes of a data object, also called features, dimensions, variables, describe the characteristics of the data object.
5. Which of the following refers to the set of features that describe a data object?
a) Instance
b) Attribute vector
c) Data point
d) Sample
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Explanation: A data object is described by one or more attributes or features. The set of attributes or features that represent the characteristics of a data point is called an attribute vector or a feature vector.
6. Which of the following refers to the distribution of data based on two variables?
a) Bivariate distribution
b) Univariate distribution
c) Time series
d) Association rules
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Explanation: The distribution of data may depend on the attributes or variables representing the properties of the data. When the distribution of the data depends on a single variable, it is known as a univariate distribution. A bivariate distribution is the data distribution based on two variables.
7. The set of possible values an attribute can possess is determined by _____
a) Attribute vector
b) Feature vector
c) Attribute type
d) Variable
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Explanation: The type of an attribute represents the set of possible values the attribute can have. The type of an attribute can be nominal, binary, ordinal or numeric depending on the property it represents and the requirement of the task to be performed.
8. Which of the following cannot be the value of a nominal attribute?
a) Names of things
b) Symbols
c) Numbers intended for quantitative use
d) Numbers not intended for quantitative use
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Explanation: The nominal attributes are used to represent some kind of category or code. The names of things, symbols, and numbers not intended for quantitative use are some of the values that a nominal attribute can have.
9. Nominal attributes are also called categorical attributes.
a) True
b) False
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Explanation: The nominal attributes are also known as categorical attributes because they are used to represent categories using values such as names of things, symbols or numbers which are not quantitatively used.
10. Which of the following is not true about nominal attribute values?
a) Nominal attribute values have a meaningful order
b) Nominal attribute values do not have a meaningful order
c) Nominal attribute values are not quantitative
d) Mode of nominal attribute values is a useful measure
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Explanation: The nominal attribute values are used to represent categories or codes and have no quantitative significance or a meaningful order. Due to the lack of quantitative aspect of the nominal attribute values, mean and median make no sense, but mode is considered a useful measure of central tendency, specifically, to find the most common values the of the attribute.
11. A nominal attribute with two categories is known as _____
a) Attribute vector
b) Numeric attribute
c) Binary attribute
d) Ordinal attribute
View Answer
Explanation: Nominal attributes or categorical attributes are used to represent categories or codes. Nominal attributes, when used to represent only two possible categories, are referred to as binary attributes.
12. Binary attributes, with the two categories representing true and false, are known as _____
a) Boolean attributes
b) Numeric attributes
c) Ordinal attributes
d) Interval scaled
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Explanation: The binary attributes are the nominal attributes with two categories. When these categories represent true or false for the attribute values, they are referred to as Boolean attributes.
13. The binary attributes with both the categories having equal importance are called as _____
a) Symmetric
b) Asymmetric
c) Ordinal
d) Numeric
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Explanation: The two categories of a binary attribute may indicate the presence or absence of the attribute. The two states of symmetric binary attribute carry equal importance whereas, one state is more important than the other in case of asymmetric binary attribute.
14. The more important state of a binary attribute must be coded one and the other should be coded zero.
a) True
b) False
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Explanation: The more important state of a binary attribute is conventionally coded as one and the less important state is conventionally coded as zero, but it is not compulsory. It is the wish of the programmer to give the codes as per the required task.
15. Which of the following is not a qualitative attribute type?
a) Nominal
b) Ordinal
c) Binary
d) Numeric
View Answer
Explanation: The values of a qualitative attribute do not have quantitative significance and applying mathematical operations on them does not make sense. Nominal, ordinal and binary attributes fall under this category. Numeric attributes, on the other hand, have quantitative significance.
Sanfoundry Global Education & Learning Series – Data Mining.
To practice all areas of Data Mining, here is complete set of Multiple Choice Questions and Answers.
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