Skip to content

Tag: classification

SKLearn & ElasticNet: Cross validation fails when using Accuracy as a metric

I have a binary classification problem. I’ve been using cross validation to optimize the ElasticNet parameters. However ElasticNet only seems to work when I supply roc_auc as the scoring method to be used during CV, However I also want to test out a wide range of scoring methods, in particular accuracy. Specifically, when using accuracy, ElasticNet returns this error: However

Does my learning curves show overfitting? [closed]

Closed. This question is not about programming or software development. It is not currently accepting answers. This question does not appear to be about a specific programming problem, a software algorithm, or software tools primarily used by programmers. If you believe the question would be on-topic on another Stack Exchange site, you can leave a comment to explain where the

SHAP Linear model waterfall with KernelExplainer and LinearExplainer

I am working on binary classification and trying to explain my model using SHAP framework. I am using logistic regression algorithm. I would like to explain this model using both KernelExplainer and LinearExplainer. So, I tried the below code from SO here This threw an error as shown below AssertionError: Unknown type passed as data object: <class ‘shap.maskers._tabular.Independent’> How can