# Giving a score (from 1 - 5) using weights

I have a dataset with 8 features (columns). Each row is a customer, for which I want to give a score from 1-5 using the 8 features for each customer. The range of values are as follows:

Feature 1: 0-19

Feature 2: 0 - 4651107

Feature 3: 0 - 3525

Feature 4: binary (0 or 1)

Feature 5: binary (0 or 1)

Feature 6: binary (0 or 1)

Feature 7: binary (0 or 1)

Feature 8: 0 - 25857

I tried giving each feature a weight (from 0 to 1). So, the most important feature will have a weight of 0.9, then 0.85, then 0.8, etc... Then the score is given by:

Score = $\lambda_1x_1$+$\lambda_2x_2$+...+$\lambda_8x_8$ where $\lambda$ are the weights for each feature $x$

I need to somehow scale the final scores from 1-5, which I failed on doing. I'd appreciate an opinion on either of the below:

1) If you think my method is flawed due to the ranges of each features, or something else, please suggest a way from scratch to get the scores :)

2) If you think my method of linear combinations works, then please suggest how to scale the scores from 1-5 :)

3) Anything else! Maybe KNN or something? I don't really know haha

Thank you all very much.

• Don't you think that we can get the coefficients of each col after applying LR and yes the scales will fool the LR, su rescale properly – Aditya Jul 6 '18 at 2:37
• @Aditya Thanks Aditya! How would the LR work here? To get the coefficients :) – Programmer Jul 6 '18 at 3:38