R Square and Adjusted R Square

R Square:-

R square is also known as Coefficient of Determination.

It is used to check the goodness of best fit line.

Normally, we get our R Square value between 0 to 1.

The R Square value is more nearer to 1 it shows that our line is best fitted to the model.

But when our best fit line is become a worser than average best fit line at that time our R Square became a negative value.

When we are adding more and more independent variable whether it is correlated to the target variable or not, our R Square value will always increases.Its never decreases.

It is not penalizing the new added independent variable which are not correlated.

For penalizing the new added independent variable which are not correlated we use Adjusted RSquare.

Adjusted R Square:-

It is penalizes the independent variable that r not correlated.

When we are adding more and more independent variable which is correlated to the target variable at that time our Adjusted R Square value is increases.

But when we are adding more and more independent variable which is not correlated to the target variable at that time our Adjusted R Square value is decreases.

Note:-

Adjusted R Square value is always less than or equal to R Square value.

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