I tried PyCaret2.0 (pycaret-nightly)

Introduction

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How to try

pip install pycaret-nightly

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try

Preprocessing for imbalanced data

from pycaret.classification import *
exp1 = setup(
    data, 
    target = 'default',
    fix_imbalance=True #Add this line
)

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Pretreatment performed (SMOTE)

Other pretreatment

fix_imbalance_method: obj, default = None
When fix_imbalance is set to True and fix_imbalance_method is None, 'smote' is applied 
by default to oversample minority class during cross validation. This parameter
accepts any module from 'imblearn' that supports 'fit_resample' method.

How to specify other preprocessing

from pycaret.classification import *
from imblearn.over_sampling import ADASYN, BorderlineSMOTE, KMeansSMOTE, RandomOverSampler, SMOTE, SMOTENC, SVMSMOTE
exp1 = setup(
    data, 
    target = 'default',
    fix_imbalance=True,
    fix_imbalance_method=ADASYN() #Specified on this line
)

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Algorithm that could be specified

Ingenuity on display when evaluating a model

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Finally

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