- 2019-08-17 10:29
*views 2*- machine learning

According to can study , How to measure and present , There are different ways to describe variables .

** Numerical variable (Numeric)** There are values that describe measurable quantities as numbers , for example “ How many? ” or “ How many? ”. therefore , Numerical variables are quantitative variables (quantitative).

Numerical variables can be further described as continuous or discrete ：

* continuous variable (continuous)

It's a numeric variable . Observations can take any value between a set of real numbers . Observations given to continuous variables may include values as small as permitted by the measuring instrument . Examples of continuous variables include height , time , Age and temperature .

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** discrete variable (discrete)** It's a numeric variable . Observations can obtain values based on counts from a different set of global values . Discrete variables cannot take a fraction between one value and the next closest value . Examples of discrete variables include the number of registered vehicles , The number of business locations and the number of children in the family , All of these are integrated units （ Namely 1,2,3 Cars ） measure .

Categorical variable (Categorical)

With description data unit “ quality ” or “ features ” Value of , for example “ What type ” or “ Which category ”. Categorical variables are mutually exclusive （ In one category or another ） And detail （ Include all possible options ） category . therefore , The categorical variable is

Qualitative variable (qualitative), And tend to be represented by non numeric values .

Categorical variables can be further described as ordinal or nominal ：

* ordinal variable (ordinal)

It's a categorical variable . Observations can take values that can be logically sorted or sorted . The category associated with an ordinal variable can be higher or lower than the other , But it doesn't necessarily create a numerical difference between each category . Examples of ordered categorical variables include academic achievement （ Namely A,B,C）, Clothing scale （ That is small , in , large , Extra large ） And attitude （ I agree with you very much , agree! , disagree , Strongly disagree ）.

* Nominal variable (nominal) It's a categorical variable . Observations can take values that cannot be organized in logical order . Examples of nominal categorical variables include gender , Business type , Eye color , Religion and brand .

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