k-fold target encoding
Table of Contents
bayesian target encoding but split the training set to k equal size parts, and encode each part’s feature with all other parts target values.
So for
name | favorite color | height | net worth |
james | red | 1.7 | 5000 |
josh | blue | 1.8 | 4000 |
johnathan | red | 1.7 | 7000 |
joe | blue | 1.8 | 6000 |
joel | blue | 1.8 | 5000 |
johnas | red | 1.7 | 5000 |
with k = 3,
name | favorite color | height | net worth |
---|---|---|---|
james | red | 1.7 | 5000 |
josh | blue | 1.8 | 4000 |
johnathan | red | 1.7 | 7000 |
joe | blue | 1.8 | 6000 |
joel | blue | 1.8 | 5000 |
johnas | red | 1.7 | 5000 |
James’ red value is encoded with only
name | favorite color | height | net worth |
---|---|---|---|
johnathan | red | 1.7 | 7000 |
joe | blue | 1.8 | 6000 |
joel | blue | 1.8 | 5000 |
johnas | red | 1.7 | 5000 |
And joe’s blue with only
name | favorite color | height | net worth |
---|---|---|---|
james | red | 1.7 | 5000 |
josh | blue | 1.8 | 4000 |
joel | blue | 1.8 | 5000 |
johnas | red | 1.7 | 5000 |
1. refrencde
statquest. k=5 works?
Backlinks
target encoding
To encode the discrete-valued feature with the target value we are trying to pridict.
leave-one-out target encoding
k-fold target encoding in which each fold contains only 1 row, so that row’s feature’s encoding is calculated with bayesian target encoding for that feature of all other rows.