Using PermutationImportance with LGBMClassifier causes ValueError: Unknown label type: 'continuous'

Question

我想得到 eli5 的特征排列分数，但不断得到 ValueError: Unknown label type: 'continuous' 我该如何解决？

import eli5
from eli5.sklearn import PermutationImportance
from sklearn.svm import SVC
from sklearn.feature_selection import SelectFromModel
my_model = RandomForestClassifier()

# ... load data
clf = lgb.LGBMClassifier(nthread=4,            boosting_type= 'gbdt', 
            metric= 'auc', n_estimators= 5000    )
perm = PermutationImportance(clf, cv=5)
perm.fit(df[feat], df.CSI)

# perm.feature_importances_ attribute is now available, it can be used
# for feature selection - let's e.g. select features which increase
# accuracy by at least 0.05:
sel = SelectFromModel(perm, threshold=0.05, prefit=True)
X_trans = sel.transform(X)

Answer 1

已解决问题：

perm.fit(df[feat].values, df.CSI.values)

Using PermutationImportance with LGBMClassifier causes ValueError: Unknown label type: 'continuous'

Using PermutationImportance with LGBMClassifier causes ValueError: Unknown label type: 'continuous'

python

permutation

python-3.x

valueerror

lightgbm