DWDM \ Types of Attributes
Association Mining Rules: Nominal, Ordinal, Interval and Ratio.
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Types of Attribute |
Details |
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Nominal |
These are names used to distinguish names
or objects. Examples Attribute1= ID Attribute1 vaules = numbers= (ASS01,ASS02….), Attribute1 = zip codes
e.t.c |
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Ordinal |
These are used to scale the values. Example for rankings grades(A,B,C and D),
height in {tall, medium, short} e.t.c |
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Interval |
Here the difference between the values will be meaningful. Examples Calendar
dates, temperatures in Celsius or Fahrenheit. |
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Ratio |
Here the differences or ratio of variables values will be meaningful. Example
temperature in Kelvin, length, time, counts |
Discrete and Continuous Attributes
Discrete Attribute
It has only a finite or countably infinite set of values and are represented as integer variables.
Examples: binary attributes, zip codes, counts, or the set of words in a collection of documents.
Continuous Attribute
It has real numbers as attribute values represented asa finite number of digits / floating-point variables.
Examples: temperature, height, or weight.
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