A variable is a characteristic, number, or quantity that can be measured or counted. Most variables in a dataset are either numerical or categorical. Numerical variables take numbers as values and can be discrete or continuous, whereas for categorical variables, the values are selected from a group of categories, also called labels.
Variables in their original, raw format are not suitable to train machine learning algorithms. In fact, we need to consider many aspects of a variable to build powerful machine learning models. These aspects include variable type, missing data, cardinality and category frequency, variable distribution and its relationship with the target, outliers, and feature ...
