Diagram
AttributeError: ‘SMOTE’ object has no attribute ‘fit_sample’ error occurs when you “try to call the fit_sample() method on a SMOTE object from the imbalanced-learn library, but it does not exist.”
To fix the AttributeError: ‘SMOTE’ object has no attribute ‘fit_sample’ error, use the “fit_resample()” method instead of “fit_sample()” method.
Reproduce the error
from imblearn.over_sampling import SMOTE
from sklearn.datasets import make_classification
# Create a sample imbalanced dataset
X, y = make_classification(n_classes=2, class_sep=2,
weights=[0.1, 0.9], n_informative=3, n_redundant=0,
flip_y=0, n_features=5, n_clusters_per_class=1,
n_samples=1000, random_state=42)
# Create a SMOTE object
smote = SMOTE(random_state=42)
# Fit and resample the dataset using SMOTE
X_resampled, y_resampled = smote.fit_sample(X, y)Output
AttributeError: 'SMOTE' object has no attribute 'fit_sample'
How to fix it?
Replace the fit_sample() call with the fit_resample() method, which should resolve the issue.
from imblearn.over_sampling import SMOTE
from sklearn.datasets import make_classification
# Create a sample imbalanced dataset
X, y = make_classification(n_classes=2, class_sep=2,
weights=[0.1, 0.9], n_informative=3, n_redundant=0,
flip_y=0, n_features=5, n_clusters_per_class=1,
n_samples=1000, random_state=42)
# Create a SMOTE object
smote = SMOTE(random_state=42)
# Fit and resample the dataset using SMOTE
X_resampled, y_resampled = smote.fit_resample(X, y)
If you run the above code, it won’t give you any error!
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Krunal Lathiya is a seasoned Computer Science expert with over eight years in the tech industry. He boasts deep knowledge in Data Science and Machine Learning. Versed in Python, JavaScript, PHP, R, and Golang. Skilled in frameworks like Angular and React and platforms such as Node.js. His expertise spans both front-end and back-end development. His proficiency in the Python language stands as a testament to his versatility and commitment to the craft.
