Objective and explanatory variables

What is an objective variable?

An objective variable is a variable that you want to find (predict) in supervised learning in machine learning.

What is an explanatory variable?

The explanatory variables are the variables that act on the objective variable in supervised learning of machine learning.

Examples

Suppose you want to create a machine learning model to predict the price of a building, and you have the following data as an example of supervised data.

In this case, the price is the objective variable. In this case, the price is the objective variable, and the variables that affect the price are other than the objective variable, so these are called explanatory variables.

In this case, the price is the objective variable.
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If a human being predicts the rent of a rental house, etc., even a person outside the real estate industry may be able to understand sensibly that the price will fall if the house is far from the station, or if the building is old.
And, in general, when the person who predicts is the person of the real estate industry, it is thought that there are many cases where it has wider and deeper knowledge than the person who is not so.
If you have broad and deep knowledge, you can imagine that there are many cases where the price you forecast is also more accurate.

This kind of knowledge is called domain knowledge, and it is very important in creating machine learning models.


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