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Data Mining > Data > Flashcards

Data Flashcards

1
Q

is a collection of data objects and their attributes.

A

Data

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2
Q

is a property or characteristics of an object.

A

Attribute

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3
Q

is described by a collection of attributes.

A

Object

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4
Q

are numbers or symbols assigned to an attribute.

A

Attribute Values

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5
Q

4 TYPES OF ATTRIBUTE SCALES

A
  1. Nominal
  2. Ordinal
  3. Interval
  4. Ratio
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6
Q

is a scale that provides only enough information to distinguish one object from another.

A

Nominal

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7
Q

is a scale that provides enough information to order objects.

A

Ordinal

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8
Q

is a scale that provides the differences between values are meaningful, a unit of measurement exists.

A

Interval

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9
Q

is a scale that provides both differences and ratios are meaningful.

A

Ratio

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10
Q

is an attribute that has only finite or countably infinite set of values. Are represented as integer variables.

A

Discrete Attributes

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11
Q

is an attribute that has real numbers as attribute values. Are represented by floating point variables.

A

Continuous Attributes

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12
Q

3 TYPES OF DATA SETS

A
  1. Record
  2. Graph
  3. Ordered
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13
Q

data that consists of a collection of records each of which consists of a fixed set of attributes.

A

Record

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14
Q

3 EXAMPLES OF A RECORD

A
  • Data Matrix
  • Document Data
  • Transaction Data
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15
Q

2 EXAMPLES OF A GRAPH

A
  • World Wide Web
  • Molecular Structures
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16
Q

4 EXAMPLES OF AN ORDERED DATA SET

A
  • Spatial Data
  • Temporal Data
  • Sequential Data
  • Genetic Sequence Data
17
Q

4 EXAMPLES OF DATA QUALITY PROBLEMS

A
  1. Noise
  2. Outliers
  3. Missing Values
  4. Duplicate Data
18
Q

refers to modification of original values.

A

Noise

19
Q

are data objects with characteristics that are considerably different than most of the other data objects in the dataset.

A

Outliers

20
Q

is a process of dealing with duplicate data.

A

Data Cleaning

Data Mining (9 decks)

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