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Emre
Emre
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Difference between R squaredcoefficient of determination and Leastleast squared error?

Where and when should I consider R squaredR^2 as a goodnessmeasure of goodness-of-fit for regressions?
Usually I choose the least squared model as the best model.
Is it possible that the least squared model does not have the highest R squared?
Should I use both as the evaluation of regressions?
Could you give me an intuitive example?

Difference between R squared and Least squared error?

Where and when should I consider R squared as a goodness of regressions?
Usually I choose the least squared model as the best model.
Is it possible that the least squared model does not have the highest R squared?
Should I use both as the evaluation of regressions?
Could you give me an intuitive example?

Difference between coefficient of determination and least squared error?

Where and when should I consider R^2 as a measure of goodness-of-fit for regressions?
Usually I choose the least squared model as the best model.
Is it possible that the least squared model does not have the highest R squared?
Should I use both as the evaluation of regressions?
Could you give me an intuitive example?

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Kaggle
Kaggle
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Difference between R squared and Least squared error?

Where and when should I consider R squared as a goodness of regressions?
Usually I choose the least squared model as the best model.
Is it possible that the least squared model does not have the highest R squared?
Should I use both as the evaluation of regressions?
Could you give me an intuitive example?