Describe the issue linked to the documentation

I am trying to leverage the classification metrics that rely on a posterior probability (i.e. P(Y | X=x)). This is commonly named y_pred_proba in the sklearn API.

However, I noticed a discrepancy in the naming of the argument for this in various metrics. For example:

• https://scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_recall_curve.html#sklearn.metrics.precision_recall_curve names is probas_pred
• https://scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html#sklearn.metrics.roc_auc_score names is y_score
• https://scikit-learn.org/stable/modules/generated/sklearn.metrics.brier_score_loss.html#sklearn.metrics.brier_score_loss is y_prob
• https://scikit-learn.org/stable/modules/generated/sklearn.metrics.top_k_accuracy_score.html#sklearn.metrics.top_k_accuracy_score is y_score

Based on the glossary, only y_score has anything related by ctrl+f.

Suggest a potential alternative/fix

Perhaps we can name them all y_score to be consistent? E.g. the following two metrics

• https://scikit-learn.org/stable/modules/generated/sklearn.metrics.brier_score_loss.html#sklearn.metrics.brier_score_loss
• https://scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_recall_curve.html#sklearn.metrics.precision_recall_curve