How to identify a Linear Regression Problem in ML?

Use these 3 simple techniques

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1/ Linear relationship

Look for a linear relationship between the independent (predictor) variables and the dependent (outcome) variable.

Ex: The price of a house has a linear relationship to the size (sq ft) of the house.
When the size increases the price also increases.

2/ Continous Outcome Variable

The outcome variable is continuous (i.e., a numeric value that can take on any value within a certain range)

Ex: Predicting the stock price (Continous Outcome Variable) of a company based on the economical indicators.

3/ No clear pattern

Another way to identify a linear regression problem is to look for a lack of clear patterns or relationships between the variables.

If your dataset has no sure relationship between the variables, a regression can be a good way to understand the relationships

That's a wrap!

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