Different result with roc_auc_score () and auc () - Stack Overflow
I have trouble understanding the difference (if there is one) between roc_auc_score() and auc() in scikit-learn. Im tying to predict a binary output with imbalanced classes (around 1.5% for Y=1).
What is the difference between cross_val_score with …
2015年11月11日 · I am also totally confused by this difference. I also tried using the standard make_scorer() function that turn a score function into a correct Scorer object for …
python - Scikit-learn : roc_auc_score - Stack Overflow
2015年6月3日 · I am using the roc_auc_score function from scikit-learn to evaluate my model performances. Howver, I get differents values whether I use predict() or predict_proba() …
How to get roc auc for binary classification in sklearn
from sklearn.metrics import make_scorer from sklearn.metrics import roc_auc_score myscore = make_scorer(roc_auc_score, needs_proba=True) from sklearn.model_selection import …
ROC AUC score for AutoEncoder and IsolationForest
2019年11月17日 · sklearn.metrics.roc_auc_score(y_true, y_score, average=’macro’, sample_weight=None, max_fpr=None y_true : True binary labels or binary label indicators. …
python - Using cross validation and AUC-ROC for a logistic …
2017年5月18日 · So if you chose f1-score for example, the model predictions generated during cross-val-score would be class predictions (from the model's predict() method). And if you …
python - Manually calculate AUC - Stack Overflow
2018年6月14日 · Yes, it is possible to obtain the AUC without calling roc_curve. You first need to create the ROC (Receiver Operating Characteristics) curve. To be able to use the ROC curve, …
roc_auc_score mismatch between y_test and y_score
2020年7月28日 · ROC AUC score is not defined in that case. In this case, there is only one class present in y_true because the roc_auc_score function iterates over each class (identified as …
Which is the correct way to calculate AUC with scikit-learn?
2021年2月27日 · so for your question metrics.plot_roc_curve(classifier, X_test, y_test, ax=plt.gca()) may be using default predict_proba() to predict the auc, and for …
python - Finding AUC score for SVM model - Stack Overflow
2021年1月17日 · You don't really need probabilities for the ROC, just any sort of confidence score. You need to rank-order the samples according to how likely they are to be in the …