setup and compare model function in regression in pycaret

This recipe explains the setup compare model function in regression in pycaret. The Setup function initializes the training environment and The Compare model function trains and evaluates performance of all estimators

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Recipe Objective - What are the setup and compare_models functions in the regression model in pycaret?

PyCaret provides setup and compare_models function in the regression module.

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Setup function with Example:-

PyCaret provides "pycaret.regression.setup()" function. The Setup function initializes the training environment and creates the transformation pipeline.

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from pycaret.datasets import get_data
juice = get_data('juice')
# importing regression module
from pycaret.regression import *
# initialize the setup
setup_name = setup(data = juice, target = 'Purchase')

compare_models function with Example:-

PyCaret provides "pycaret.regression.compare_models()" function. The Compare model function trains and evaluates performance of all estimators in the model library.

The output of this function is a score grid with average cross validated scores.

from pycaret.datasets import get_data
juice = get_data('juice')
# importing regression module
from pycaret.regression import *
# initialize the compare model
exp_name = setup(data = juice, target = 'Purchase')
comp_model = compare_models()

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