vastorbit.machine_learning.memmodel.preprocessing.MinMaxScaler.transform_sql

MinMaxScaler.transform_sql(X: Annotated[list | ndarray, 'Array Like Structure']) → list[str]

Transforms and returns the SQL needed to deploy the Scaler.

Parameters:

X (ArrayLike) – The names or values of the input predictors.

Returns:

SQL code.

Return type:

list

Examples

Import the required module.

from vastorbit.machine_learning.memmodel.preprocessing import StandardScaler

We will use the following attributes:

mean = [0.4, 0.1]
std = [0.5, 0.2]

Let’s create a model.

model_sts = StandardScaler(mean, std)

Let’s use the following column names:

cnames = ['col1', 'col2']

Get the SQL code needed to deploy the model.

model_sts.transform_sql(cnames)

Important

For this example, a specific model is utilized, and it may not correspond exactly to the model you are working with. To see a comprehensive example specific to your class of interest, please refer to that particular class.