Calibrate the model with PyCaret

Introduction

Make a model

Data loading

from pycaret.datasets import get_data
diabetes = get_data('diabetes')

image.png

Modeling using a decision tree

#Import classification package
from pycaret.classification import *
clf1 = setup(data = diabetes, target = 'Class variable')

#Make a decision tree
dt = create_model(estimator='dt')

#Visualization
evaluate_model(dt)

Check the Calibration Curve before calibration

image.png

Calibrate the model

#Calibrate
calibrated_dt = calibrate_model(dt)

#Visualize
evaluate_model(calibrated_dt)

image.png

What is the calibration done?

image.png

Which model needs calibration "Yes?"

algorithm Before calibration After calibration
Logistic
Regression
download.png download.png
RBF SVM download.png download.png
Random
Forest
download.png download.png
XGBoost download.png download.png
LightGBM download.png download.png

Finally

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