Generating artificial data to extend learning set

I have dataset containing 42 instances(X) and one final Y on which i want to perform LASSO regression.All are continuous and numerical. As the sample size small, I wish to extend it. I am kind of aware of algorithms like SMOTE used for extending imbalanced dataset. Is there anything available for my case where there is no imbalance?

Topic lasso data regression sampling dataset

Category Data Science

1
answered at

SMOTE can be used to resample any continuous dataset, imbalanced or not.

If you use the Python implementation of SMOTE, sampling_strategy can be set to 'all' which resamples all classes.

Something like:

from imblearn.over_sampling import SMOTE

sm = SMOTE(sampling_strategy='all')
X_res, y_res = sm.fit_resample(X, y)

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