Using FsPlot, I plotted the data of the cars and the miles per gallon as a scatter plot:
So for each data point, I plotted a dot and then plotted the predicted value of the miles per gallon (the prediction was performed using multiple linear regression).
The following code renders the chart:
As a measure to find out whether the model is working better or not, you can find out the average residual value. A residual is the difference between the actual value and the predicted value. So for our example of miles per gallon dataset for multiple linear regression, the average residual can be calculated as follows:
When executed in the F# interactive, this produces the following output. To save space, I have taken only the first five rows.
From this you can see that for the first record, the actual MPG value was 18 and the predicted value was 15.377 roughly. So the residual for this entry is about 2.623. The smaller the average residual, the better the...
