Skip to main content

Variables Types

We need to now the variables types to better use and choose the right algorithms.

Variables Types

Numerical Variables

  • Continuous Variables: Variables that can take any value within a range. Examples include height, weight, temperature, etc. Real numbers.

  • Discrete Variables: Variables that can take only specific values. Examples include the number of children in a family, the number of cars in a parking lot, etc. Integers.

Categorical Variables (Strings)

  • Nominal Variables: Variables that have two or more categories, but there is no intrinsic order. Examples include gender, eye color, etc.

  • Ordinal Variables: Variables that have two or more categories with a clear order or ranking. Examples include education level (high school, college, graduate), income level (low, medium, high), etc.

When working with machine learning algorithms, it is essential to encode categorical variables into numerical values. This process is known as encoding or feature encoding.