attributes types in data mining

What is Attribute?

The attribute is the property of the object. The attribute represents different features of the object. 

Example:

In this example, RollNo, Name, and Result are attributes of the object student.

RollNo Name Result
1 Ali Pass
2 Akram Fail

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Types Of attributes

  • Binary
  • Nominal
  • Numeric
    • Interval-scaled
    • Ratio-scaled

Nominal data:

Nominal data is in alphabetical form and not in integer.

Example:

Attribute Value
Categorical data Lecturer, Assistant Professor, Professor
States New, Pending, Working, Complete, Finish
Colors Black, Brown, White, Red

Binary data:

Binary data have only two values/states.

Example:

Attribute Value
HIV detected Yes, No
Result Pass, Fail

Binary attribute is of two types;

  1. Symmetric binary
  2. Asymmetric binary
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Symmetric data:

Both values are  equally important

Example:

Attribute Value
Gender Male, Female

Asymmetric data:

Both values are  not equally important

Example:

Attribute Value
HIV detected Yes, No
Result Pass, Fail

 

Ordinal data:

All Values have a meaningful order. 

Example:

Attribute Value
Grade A, B, C, D, F
BPS- Basic pay scale 16, 17, 18

 

Discrete Data:

Discrete data have finite value. It can be in numerical form and can also be  in categorical form.

Example:

Attribute Value
Profession Teacher, Bussiness Man, Peon etc
Postal Code 42200, 42300 etc

Continuous data:

Continuous data technically have an infinite number of steps.

Continuous data is in float type. There can be many numbers in between 1 and 2

Example:

Attribute Value
Height 5.4…, 6.5….. etc
Weight 50.09….  etc
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