Challenge: Solving Task Using Regularisation
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Your task is to create a classification model using L2 regularization on the breast_cancer dataset. It contains features computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. The task associated with this dataset is to classify the breast mass as malignant (cancerous) or benign (non-cancerous) based on the extracted features.
Your task is to:
- Specify argument at the
LogisticRegression()constructor:- specify
penaltyargument equal tol2; - specify
Cargument equal to1.
- specify
- Fit regularized model on the training data.
Ratkaisu
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Completion rate improved to 6.67Challenge: Solving Task Using Regularisation
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Your task is to create a classification model using L2 regularization on the breast_cancer dataset. It contains features computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. The task associated with this dataset is to classify the breast mass as malignant (cancerous) or benign (non-cancerous) based on the extracted features.
Your task is to:
- Specify argument at the
LogisticRegression()constructor:- specify
penaltyargument equal tol2; - specify
Cargument equal to1.
- specify
- Fit regularized model on the training data.
Ratkaisu
Vaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoistaKiitos palautteestasi!
Awesome!
Completion rate improved to 6.67single
