What is the difference between simple and multiple linear regression?
Simple regression uses one input variable, while multiple regression uses two or more input variables to make predictions.
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When the model learns noise in the training data, leading to a complex line that performs poorly on test data.
No, it is used for continuous numerical predictions. For categories, use Logistic Regression.
It means 85% of the variance in the target variable is explained by the input features in your model.
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