New Function
This is a new function introduced in PyCaret 2.0x.
AutoML
This function returns the best model out of all models created in the current active environment based on metric defined in optimize parameter. Run this code at the end of your script.
This function is only available in pycaret.classification and pycaret.regression modules.
Example
Code
# loading dataset
from pycaret.datasets import get_data
data = get_data('diabetes')
# initializing setup
from pycaret.classification import *
clf1 = setup(data, target = 'Class variable')
# compare all baseline models and select top 5
top5 = compare_models(n_select = 5)
# tune top 5 base models
tuned_top5 = [tune_model(i) for i in top5]
# ensemble top 5 tuned models
bagged_top5 = [ensemble_model(i) for i in tuned_top5]
# blend top 5 base models
blender = blend_models(estimator_list = top5)
# select best model
best = automl(optimize = 'Recall')
Output
No output. Best performing model returned.
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