sklearn 中 roc_curve () 函数使用方法是什么？ - 知乎
sklearn.metrics.roc_curve() 函数是用于计算二分类问题中的接收者操作特征曲线（ROC 曲线）以及对应的阈值。 ROC 曲线是以假阳性率（False Positive Rate, FPR）为横轴，真阳性 …
Probability threshold in ROC curve analyses - Cross Validated
Nov 11, 2023 · The path along the ROC curve is equivalent to a path along the values of that linear predictor (or its associated predicted probabilities). Using a high predicted probability as …
ROC vs precision-and-recall curves - Cross Validated
The ROC curve has the unique property that the diagonal (TPR=FPR) represents chance, that the Distance above the Chance line (DAC) represents Informedness or the probability of an …
ROC vs Precision-recall curves on imbalanced dataset
Feb 18, 2017 · ROC curves can sometimes be misleading in some very imbalanced applications. A ROC curve can still look pretty good (ie better than random) while misclassifying most or all …
How to determine the best model based on ROC curves
Apr 21, 2020 · The ROC curves are giving you a measure on the degree of separability of both classes by a model, that is, how well it can distinguish both classes. The curves that you see …
How to make a ROC curve for multiple parameters/thresholds
Jan 30, 2018 · 2 You are showing individual ROC curves for each predictor, but I assume you have a multivariate model (e.g., logistic regression). What you should be showing is the ROC …
regression - How to interpret a ROC curve? - Cross Validated
Dec 1, 2014 · The area under the ROC-curve is a measure of the total discriminative performance of a two-class classifier, for any given prior probability distribution. Note that a specific …
How is an ROC curve constructed for a set of data?
Dec 30, 2015 · A ROC Curve is not constructed for a set of data, it is constructed for the results of a classification performed on a set of data. There are models (or methods of implementing …
machine learning - How to determine the optimal threshold for a ...
Nov 8, 2014 · Draw the final ROC curve Some details can be checked in . Besides, these two links are useful about how to determine an optimal threshold. A simple method is to take the …
r - Understanding ROC curve - Cross Validated
I'm having trouble understanding the ROC curve. Is there any advantage / improvement in area under the ROC curve if I build different models from each unique subset of the training set and …