When scikit-learn tests the effectiveness of their model training, they usually construct fake datasets where they know the underlying model (coefficients). They have two functions, they are
make_regression (https://scikit-learn.org/stable/modules/generated/sklearn.datasets.make_regression.html)
make_classification (https://scikit-learn.org/stable/modules/generated/sklearn.datasets.make_classification.html#sklearn.datasets.make_classification)
We should do the same. This is issue tracks our implementation of makeRegression and makeClassification which will be helpful for testing the speed and efficacy of our models.
When scikit-learn tests the effectiveness of their model training, they usually construct fake datasets where they know the underlying model (coefficients). They have two functions, they are
make_regression (https://scikit-learn.org/stable/modules/generated/sklearn.datasets.make_regression.html)
make_classification (https://scikit-learn.org/stable/modules/generated/sklearn.datasets.make_classification.html#sklearn.datasets.make_classification)
We should do the same. This is issue tracks our implementation of
makeRegressionandmakeClassificationwhich will be helpful for testing the speed and efficacy of our models.