ValueError: unknown is not supported in sklearn.RFECV

When using the Scikit-learn RFECV (Recursive Feature Elimination with Cross-Validation) module, you may come across a ValueError with the message "unknown is not supported in sklearn.RFECV". This error occurs when you try to use an unsupported estimator within the RFECV module.

Possible Causes

There are a few possible causes for this error:

1. Using an unsupported estimator: The RFECV module only supports certain estimators, and if you try to use an unsupported estimator, you will get this error. For example, if you try to use a non-linear estimator or an estimator that doesn't have a coef_ attribute, you will get this error.

2. Using an estimator that is not compatible with cross-validation: Some estimators are not compatible with cross-validation, which is used by the RFECV module. If you try to use one of these estimators, you will get this error.

Solutions

There are a few solutions to this problem:

1. Use a supported estimator: To avoid this error, make sure you are using a supported estimator within the RFECV module. Check the Scikit-learn documentation to see a list of supported estimators.

2. Use a compatible estimator: If you must use an estimator that is not supported by RFECV, make sure it is compatible with cross-validation. You may need to implement your own cross-validation or use a different module that supports your estimator.

Example Code

Here is an example of how to use the RFECV module with a supported estimator:

from sklearn.datasets import make_classification
from sklearn.linear_model import LogisticRegression
from sklearn.feature_selection import RFECV

X, y = make_classification(n_samples=1000, n_features=10, n_informative=5, n_redundant=0, random_state=1)
logreg = LogisticRegression()
rfecv = RFECV(estimator=logreg, step=1, cv=5, scoring='accuracy')
rfecv.fit(X, y)

In this example, we are using the LogisticRegression estimator, which is a supported estimator within the RFECV module. We then fit the RFECV module to our data and perform feature selection using cross-validation.

Conclusion

The "unknown is not supported in sklearn.RFECV" error occurs when you try to use an unsupported estimator within the RFECV module. To avoid this error, make sure you are using a supported estimator or an estimator that is compatible with cross-validation.