Python PyCaret Plot Model














































Python PyCaret Plot Model




Plot Model

 
Plot Model function is used to evaluate performance of the trained machine learning model. Here is an example:

# import classification module
from pycaret.classification import *
# init setup
clf1 = setup(data, target = 'name-of-target')
# train adaboost model
adaboost = create_model('ada')
# AUC plot
plot_model(adaboost, plot = 'auc')
# Decision Boundary
plot_model(adaboost, plot = 'boundary')
# Precision Recall Curve
plot_model(adaboost, plot = 'pr')
# Validation Curve
plot_model(adaboost, plot = 'vc')

plot_model.py 

Figure

Sample output from plot_model function

 

Click here to learn more about different visualization in PyCaret.

Alternatively, you can use evaluate_model function to see plots via the user interface within notebook.

Figure

evaluate_model function in PyCaret

 


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