Hi

Please see below screen shot, Suppose i have data and below blue line best fitted line.

What are techniques to optimize the error e

Thanks,

Srihari

Hi

Please see below screen shot, Suppose i have data and below blue line best fitted line.

What are techniques to optimize the error e

Thanks,

Srihari

Hi, Srihari.

From the formula you can see that it is a **“Mean squared error”** we are calculating, by which we are trying to fit a line which is having the minimum error from the true value and predicted value.

If **Y’i** is the predicted value of the **i-th sample**, and **Yi** is the corresponding true value(Ground truth),

Then the **mean squared error (MSE)** estimated over **n samples** is defined as

**MSE (Y,Y’) = [ Vi (Summation ( Yi - Y’i) ^ 2 ] / n samples .**

**Where Vi means for all i starting from 0 to (n-1) samples.**

There are other types of loss also that you will study in course.

**Mean Absolute Error, Root Mean Squared Error and R Squared.**

All the best!