Let's now take this framework and use it to predict the rating for a product. We'll limit our example to three users, person X, person Y, and person Z. We'll predict the rating of a product that person X hasn't rated, but that persons Y and Z, who are very similar to X, have rated.
We'll start with our base ratings for each user, as shown in the following table:
|
Customers |
Snarky's Potato Chips |
SoSo Smooth Lotion |
Duffly Beer |
BetterTap Water |
XXLargeLivin' Football Jersey |
Snowy Cotton Balls |
Disposos' Diapers |
|
X |
4 |
3 |
4 |
||||
|
Y |
3.5 |
2.5 |
4 |
4 |
|||
|
Z |
4 |
3.5 |
4.5 |
4.5 |
Next, we'll center the ratings:
|
Customers |
Snarky's Potato Chips |
SoSo Smooth Lotion |
