Department of Mathematics and Computer Science

• Nominal features: is a named data seperated into discrete categories which means that this data has two or more possible values (The order doesn't mean anything) and these values are not numerical (except 0,1 in binary values).
  • Examples of nominal features:
    1. Animals: Dog, Cat, Bird,  ...
    2. Colors: Black, Red, Blue, Green, ....
    3. Gender: Male, Female.
    4. Employer: Yes,No  or (0,1).
    5. ....
• Ordinal features: It has almost the same definition of nominal features, but the difference between them is that this data has a useful or meaningful order unlike the nominal features.
  • Examples of ordinal features:
    1. Education Level: Bachelor, Master,Phd ...
    2. Age categories: Junior, Senior ..
    3. ....
• Continuous features: the data has an infinite number of possible values as oposed to previous features.
  • Examples of continuous features:
    1. Age: 3, 5, 8.6 ......
    2. Salary: 18.000, 25.000, 10.000, 100.000 ...
    3. ....

- nominal features: is a data descripted by their name, like Color.

- ordinal features: is a data when we can take in compative classes, like level.

- continuous features: is a data have not exacte value in time, like age.

Three types of Features or data:

1. ordinal: is a categorical type. Observations can take a value that can be ordered or logically classified. Categories associated with ordinal variables can be ranked higher or lower than others, but do not necessarily establish a numerical difference between each category.                                                                                                                                                                            examples: academic grades (A, B, C)- clothing size (small, medium, large, very large) and attitudes (strongly agree, agree, disagree, strongly disagree).              
2. nominal: is a categorical type. Observations can take a value that can not be organized in a logical sequence.                                                                                                                                   
   examples: gender, type of business, color, religion and brand.                                      
3. continue: is a numeric type. The observations can take any value between a certain set of real numbers. The value given to an observation for a continuous variable may include values ​​as small as the measuring instrument allows.                                                                                                  
   examples: height, time, age and temperature.

1.nominal: colors :black,brown.....

                  languages:frensh,englich....

                   gender:female,male

2.ordinal: grade:a,b,c.....

                educational background:elementary,hight school.....

3.continue: temperature:-1,0.....

                   height:5.4,6.2.....

                   weight:50.33......

1.nominal:Color,classes...

2.ordinal: hight,age...

3.continue: age,time,salary...