based on the weights of the linear regression model, rank the features (note: only continuous features) in decreasing order of influence on the predictions.

A variable's value can be predicted using linear regression analysis based on the value of another variable. The dependent variable is the one you want to be able to predict. The independent variable is the one you're using to make a prediction about the value of the other variable.

Understanding linear regression is crucial because it offers a methodical way to identify and forecast future events. Numerous businesses and people can gain from the ability to find predictions and evaluate them, such as improved operations and thorough research materials.

Plotting the predicted values against the actual values in the holdout set is the most effective way to examine a regression data set. The points should, under ideal circumstances, lie on the 45-degree line that passes through the origin (y = x is the equation). The regression is better the closer the points are to this line.

Note that your information is incomplete and an overview was given.

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