如何使用 sklearn 计算具有二元相关性的 NDCG?
How to calculate NDCG with binary relevances using sklearn?
我正在尝试计算二元相关性的 NDCG 分数:
from sklearn.metrics import ndcg_score
y_true = [0, 1, 0]
y_pred = [0, 1, 0]
ndcg_score(y_true, y_pred)
并获得:
ValueError: Only ('multilabel-indicator', 'continuous-multioutput',
'multiclass-multioutput') formats are supported. Got binary instead
有没有办法让它工作?
请尝试:
from sklearn.metrics import ndcg_score
y_true = [[0, 1, 0]]
y_pred = [[0, 1, 0]]
ndcg_score(y_true, y_pred)
1.0
注意 docs 中的预期形状:
y_true: ndarray, shape (n_samples, n_labels)
y_score: ndarray, shape (n_samples, n_labels)
我正在尝试计算二元相关性的 NDCG 分数:
from sklearn.metrics import ndcg_score
y_true = [0, 1, 0]
y_pred = [0, 1, 0]
ndcg_score(y_true, y_pred)
并获得:
ValueError: Only ('multilabel-indicator', 'continuous-multioutput',
'multiclass-multioutput') formats are supported. Got binary instead
有没有办法让它工作?
请尝试:
from sklearn.metrics import ndcg_score
y_true = [[0, 1, 0]]
y_pred = [[0, 1, 0]]
ndcg_score(y_true, y_pred)
1.0
注意 docs 中的预期形状:
y_true: ndarray, shape (n_samples, n_labels)
y_score: ndarray, shape (n_samples, n_labels)