我正在使用lightGBM查找功能重要性,但是出现错误LightGBMError: b'len of label is not same with #data'
。
形状
(73147,12)
形状
(73147,)
代码:
from sklearn.model_selection import train_test_split
import lightgbm as lgb
# Initialize an empty array to hold feature importances
feature_importances = np.zeros(X.shape[1])
# Create the model with several hyperparameters
model = lgb.LGBMClassifier(objective='binary', boosting_type = 'goss', n_estimators = 10000, class_weight = 'balanced')
# Fit the model twice to avoid overfitting
for i in range(2):
# Split into training and validation set
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = i)
# Train using early stopping
model.fit(X, y_train, early_stopping_rounds=100, eval_set = [(X_test, y_test)],
eval_metric = 'auc', verbose = 200)
# Record the feature importances
feature_importances += model.feature_importances_
请参见下面的屏幕截图:
答案 0 :(得分:1)
您的代码中似乎有错字;代替
model.fit(X, y_train, [...])
应该是
model.fit(X_train, y_train, [...])
现在,X
和y_train
的长度不相同是可以理解的,因此会出现错误。