Variables are the basic building blocks of an ML algorithm. Based on these variables, the algorithm identifies and equation which will be applied on new input data. These variables are mostly of two types:
- Categorical Variables
This variable represents a field which can be classified into categories or groups.
example : sex, favorite color, age
- Numerical Variables
This variable represents a field which can be measured and sorted.
example : height, weight
Categorical variables are visualized using bar charts, frequency tables or pie charts.
Numerical variables are visualized using scatter plots or line graphs.
An interesting reference : Shodor – Numerical and Catagorical data
In my next blog, I will be writing on Supervised Learning.