{"id":202714,"date":"2024-11-22T09:32:51","date_gmt":"2024-11-22T09:32:51","guid":{"rendered":"https:\/\/namso-gen.co\/blog\/how-to-get-r-squared-value-in-python\/"},"modified":"2024-11-22T09:32:51","modified_gmt":"2024-11-22T09:32:51","slug":"how-to-get-r-squared-value-in-python","status":"publish","type":"post","link":"https:\/\/namso-gen.co\/blog\/how-to-get-r-squared-value-in-python\/","title":{"rendered":"How to get R-squared value in Python?"},"content":{"rendered":"

To get the R-squared value in Python, you can use the `sklearn` library which provides a function to calculate it. The R-squared value, also known as the coefficient of determination, is a statistical measure that represents the proportion of the variance for a dependent variable that’s explained by an independent variable.<\/p>\n

**Here is how you can get the R-squared value in Python using the `sklearn` library:**<\/p>\n

“`python
\nfrom sklearn.metrics import r2_score<\/p>\n

# Assuming y_true and y_pred are your true and predicted values
\nr_squared = r2_score(y_true, y_pred)<\/p>\n

print(“R-squared value:”, r_squared)
\n“`<\/p>\n

This will print out the R-squared value for your data, indicating how well your model fits the data.<\/p>\n

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