what does the r2_score function in scikit-learn measure when applied to a regression model? in python

The r2_score function in scikit-learn measures the coefficient of determination (R-squared) when applied to a regression model. R-squared is a statistical measure that represents the proportion of the variance in the dependent variable that is predictable from the independent variables. It provides an indication of how well the observed outcomes are replicated by the model.

Here's an example of how to use the r2_score function in Python:

main.py
from sklearn.metrics import r2_score

# Assuming y_true and y_pred are the true and predicted values from the regression model
r2 = r2_score(y_true, y_pred)
print("R-squared score:", r2)
187 chars
6 lines

In the output, the value of r2 will represent the R-squared value, with 1.0 being the best possible score indicating a perfect fit.