{"id":1046,"hash":"ea78ee12f625ba3edd4c83cf38e057bb873c0f115e68a2d9627bdc2ea1f8c8d0","pattern":"SKLearn warning "valid feature names" in version 1.0","full_message":"I'm getting the following warning after upgrading to version 1.0 of scikit-learn:\n\nUserWarning: X does not have valid feature names, but IsolationForest was\nfitted with feature name\n\nI cannot find in the docs on what is a \"valid feature name\". How do I deal with this warning?","ecosystem":"pypi","package_name":"python-3.x","package_version":null,"solution":"I got the same warning message with another sklearn model. I realized that it was showing up because I fitted the model with a data in a dataframe, and then used only the values to predict. From the moment I fixed that, the warning disappeared.\n\nHere is an example:\n\nmodel_reg.fit(scaled_x_train, y_train[vp].values)\ndata_pred = model_reg.predict(scaled_x_test.values)\n\nThis first code had the warning, because scaled_x_train is a DataFrame with feature names, while scaled_x_test.values is only values, without feature names. Then, I changed to this:\n\nmodel_reg.fit(scaled_x_train.values, y_train[vp].values)\ndata_pred = model_reg.predict(scaled_x_test.values)\n\nAnd now there are no more warnings on my code.","confidence":0.95,"source":"stackoverflow","source_url":"https://stackoverflow.com/questions/69326639/sklearn-warning-valid-feature-names-in-version-1-0","votes":105,"created_at":"2026-04-19T04:52:13.802626+00:00","updated_at":"2026-04-19T04:52:13.802626+00:00"}