OneHotEncoder¶

In [ ]:

OneHotEncoder(name: str, 
              extra_levels: dict = {}, 
              drop_first: bool = True,
              ignore_null: bool = True,
              separator: str = '_',
              column_naming: str = "indices",
              null_column_name: str = "null")

Creates a Vertica OneHotEncoder object.

Parameters¶

Name	Type	Optional	Description
name	str	❌	Name of the the model.
extra_levels	dict	✓	Additional levels in each category that are not in the input relation.
drop_first	bool	✓	If true, the first level of the categorical variable is treated as the reference level. Otherwise, every level of the categorical variable has a corresponding column in the output view.
ignore_null	bool	✓	If true, NULL values set all corresponding one-hot binary columns to NULL. Otherwise, NULL values in the input columns are treated as a categorical level.
separator	str	✓	The character that separates the input variable name and the indicator variable level in the output table. To avoid using any separator, set this parameter to null value.
column_naming	str	✓	Appends categorical levels to column names according to the specified method: indices : Uses integer indices to represent categorical levels. values/values_relaxed : Both methods use categorical level names. If duplicate column names occur, the function attempts to disambiguate them by appending _n, where n is a zero-based integer index (_0, _1,…).
null_column_name	str	✓	The string used to name the indicator column for NULL values, used only if ignore_null is false and column_naming is set to values or values_relaxed.

Attributes¶

After the object is created, all parameters become attributes. Additional attributes will be created when fitting the model:

Name	Type	Description
param_	tablesample	The OneHotEncoder parameters.
input_relation	str	Training relation.
X	list	List of the predictors.

Methods¶

Name	Description
deploySQL	Returns the SQL code needed to deploy the model.
drop	Drops the model from the Vertica DB.
fit	Trains the model.
get_attr	Returns the model attribute.
get_params	Returns the model Parameters.
set_params	Sets the parameters of the model.
to_memmodel	Converts a specified Vertica model to a memModel model.
to_python	Returns the Python code needed to deploy the model without using built-in Vertica functions.
to_sql	Returns the SQL code needed to deploy the model without using Vertica built-in functions.
transform	Applies the model on a vDataFrame.

Example¶

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from verticapy.learn.preprocessing import OneHotEncoder
model = OneHotEncoder(name = "public.OOE_Species")
display(model)

<OneHotEncoder>