# Weightings using exponents

I've got this piece of work to do where we assign weightings to different variable to achieve a score:

var A = 60%

var B = 40%

var C = 20%

var D = 5%

The score was calculated as:

$$(A^{0.6} x B^{0.4})=AB$$

$$AB^{(1-0.2)} x C^{0.2} =ABC$$

$$ABC^{(1-0.05)} x D^{0.05}$$ = final score

This worked as the first two variables being multiplied had weights = 100% so for further multiplying of variable (c) we would raise the variable to their weight (0.2) and multiply it to the previous result (AB) with the weight of 1-the weight of the variable (1-0.2) to maintain an overall weight of 100% and so on and so on.

My issue is I have to design a new feature with 5 new variables, each with a weighting of 10%.

How would I incorporate it into the model, as I can't use the logic for previous variables, as the first 2 variable weights don't add up to 100% - and so it wouldn't make sense to do (1-weights) for adding in more variables to the model?