小编kri*_*hna的帖子

我正在尝试学习如何为分类器找到最佳参数。因此，我将GridSearchCV用于多类分类问题。上生成一个虚拟的代码确实不GridSearchCV支持多级的？我只是使用 n_classes=3 的代码。

import numpy as np
from sklearn.datasets import make_classification
from sklearn.preprocessing import StandardScaler,label_binarize
from sklearn.svm import SVC
from sklearn.pipeline import make_pipeline
from sklearn.grid_search import GridSearchCV
from sklearn.metrics import accuracy_score, recall_score, f1_score, roc_auc_score, make_scorer

X, y = make_classification(n_samples=3000, n_features=10, weights=[0.1, 0.9, 0.3],n_classes=3, n_clusters_per_class=1,n_informative=2)

pipe = make_pipeline(StandardScaler(), SVC(kernel='rbf', class_weight='auto'))

param_space = dict(svc__C=np.logspace(-5,0,5), svc__gamma=np.logspace(-2, 2, 10))

f1_score
my_scorer = make_scorer(f1_score, greater_is_better=True)

gscv = GridSearchCV(pipe, param_space, scoring=my_scorer)

我正在尝试按照此处的建议进行One-hot 编码Scikit-learn GridSearch 给出 "ValueError: multiclass format is not …