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added info about scikit-learn and accuracy metrics (#30179)

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* added info about scikit-learn and accuracy metrics

Added some information about R-squared score.

* Update index.md
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Ashwin Aishvarya Vardhan
2019-05-17 20:56:21 +05:30
committed by Paul Gamble
parent 5f1e78f4d9
commit 241d966e54
1 changed files with 6 additions and 2 deletions
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guide/english/machine-learning/linear-regression/index.md
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@ -76,6 +76,10 @@ y_pred_class = model.predict(X_test)
print(metrics.accuracy_score(y_test, y_pred_class)) print(metrics.accuracy_score(y_test, y_pred_class))
``` ```
## Metrics
How would you know if your regression model is accurate or not? Well, one method is to calculate the R-squared score of your model. [R-squared score](http://blog.minitab.com/blog/adventures-in-statistics-2/regression-analysis-how-do-i-interpret-r-squared-and-assess-the-goodness-of-fit) (also known as coefficient of determination) is a statistical measure of how close the data are to the fitted regression line.
## More Information:
[scikit learn](http://scikit-learn.org/stable/documentation.html)
[Article on regression] https://www.analyticsvidhya.com/blog/2017/06/a-comprehensive-guide-for-linear-ridge-and-lasso-regression/
You can refer to this article for deeper insight into regression
https://www.analyticsvidhya.com/blog/2017/06/a-comprehensive-guide-for-linear-ridge-and-lasso-regression/