Regression

Predicting the sales amount based on month

Predicting whether a drug is effective for a patient based on her characterestics

Predicting tomorrow’s rainfall amount based on the wind speed and temperature

“Out of Sample Accuracy” is the percentage of correct predictions that the model makes on data that the model has NOT been trained on.

“Out of Sample Accuracy” is the accuracy of an overly trained model (which may captured noise and produced a non-generalized model)

When we would like to identify the strength of the effect that the independent variables have on a dependent variable.

When there are multiple dependent variables

When we would like to predict impacts of changes in independent variables on a dependent variable.

Polynomial regression models can fit using the Least Squares method.

Polynomial regression fits a curve line to your data.

Polynomial regression can use the same mechanism as Multiple Linear Regression to find the parameters.

Nonlinear regression is a method to model non linear relationship between the dependent variable and a set of independent variables.

For a model to be considered non-linear, y must be a non-linear function of the parameters.

Non-linear regression must have more than one dependent variable.

Regression >> Machine Learning with Python