What is get config function in regression model in pycaret
This recipe explains the get config function in the regression model. This function retrieves the global variables created when initializing the setup function.
Recipe Objective - What is the get_config function in the regression model in pycaret?
This module is provided by the PyCaret python library. PyCaret is an open-source, less-code machine learning python library. PyCaret automates machine learning workflow. PyCaret library is wrapped around some machine learning libraries such as sklearn, XGBoost, LightGBM, CatBoost, spaCy, Optuna, Hyperopt, Ray, and many more.
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PyCaret provides the get_config function in the regression module.
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https://www.projectpro.io/projects/data-science-projects/machine-learning-projects-in-python
get_config function with Example:-
PyCaret provides "pycaret.regression.get_config()" function. The get_config function retrieves the global variables created when initializing the setup function.
Some Accessible variables:-
X: Transformed dataset (X)
y: Transformed dataset (y)
X_train: Transformed train dataset (X)
X_test: Transformed test/holdout dataset (X)
y_train: Transformed train dataset (y)
y_test: Transformed test/holdout dataset (y)
from pycaret.datasets import get_data
bost = get_data('boston')
# importing regression module
from pycaret.regression import *
# initialize setup
set_up = setup(data = bost, target = 'medv')
X_train = get_config('X_train')
X_train
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