# get_scale_and_bias

Return the scale and bias of the model.

These values affect the results of applying the model, since the model prediction results are calculated as follows:
$\sum leaf\_values \cdot scale + bias$

## Method call format

get_scale_and_bias()

tuple

## Examples

from catboost import CatBoostRegressor, Pool
import numpy as np

train_data = [[1, 4, 5, 6],
[4, 5, 6, 7],
[30, 40, 50, 60]]

eval_data = [[2, 4, 6, 8],
[1, 4, 50, 60]]

train_labels = [10, 20, 30]

model = CatBoostRegressor()

print(model.get_scale_and_bias())

The output of this example:

(1.0, 0.0)