XGBoostError:检查失败: typestr.size() == 3 (2 vs.3)：“type vs.”应该格式为在bytes>中键入的<endian><type><size
XGBoostError:检查失败: typestr.size() == 3 (2 vs.3)：“type vs.”应该格式为在bytes>中键入的<endian><type><size
提问于 2021-04-14 15:55:17
我有一个奇怪的问题，一个新的安装xgboost。在正常情况下，它可以正常工作。但是，当我在下面的函数中使用该模型时，它会给出标题中的错误。
我使用的数据集是从kaggle借来的，可以在这里看到：https://www.kaggle.com/kemical/kickstarter-projects
用于拟合我的模型的函数如下：
def get_val_scores(model, X, y, return_test_score=False, return_importances=False, random_state=42, randomize=True, cv=5, test_size=0.2, val_size=0.2, use_kfold=False, return_folds=False, stratify=True):
print("Splitting data into training and test sets")
if randomize:
if stratify:
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, stratify=y, shuffle=True, random_state=random_state)
else:
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, shuffle=True, random_state=random_state)
else:
if stratify:
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, stratify=y, shuffle=False)
else:
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, shuffle=False)
print(f"Shape of training data, X: {X_train.shape}, y: {y_train.shape}. Test, X: {X_test.shape}, y: {y_test.shape}")
if use_kfold:
val_scores = cross_val_score(model, X=X_train, y=y_train, cv=cv)
else:
print("Further splitting training data into validation sets")
if randomize:
if stratify:
X_train_, X_val, y_train_, y_val = train_test_split(X_train, y_train, test_size=val_size, stratify=y_train, shuffle=True)
else:
X_train_, X_val, y_train_, y_val = train_test_split(X_train, y_train, test_size=val_size, shuffle=True)
else:
if stratify:
print("Warning! You opted to both stratify your training data and to not randomize it. These settings are incompatible with scikit-learn. Stratifying the data, but shuffle is being set to True")
X_train_, X_val, y_train_, y_val = train_test_split(X_train, y_train, test_size=val_size, stratify=y_train, shuffle=True)
else:
X_train_, X_val, y_train_, y_val = train_test_split(X_train, y_train, test_size=val_size, shuffle=False)
print(f"Shape of training data, X: {X_train_.shape}, y: {y_train_.shape}. Val, X: {X_val.shape}, y: {y_val.shape}")
print("Getting ready to fit model.")
model.fit(X_train_, y_train_)
val_score = model.score(X_val, y_val)
if return_importances:
if hasattr(model, 'steps'):
try:
feats = pd.DataFrame({
'Columns': X.columns,
'Importance': model[-2].feature_importances_
}).sort_values(by='Importance', ascending=False)
except:
model.fit(X_train, y_train)
feats = pd.DataFrame({
'Columns': X.columns,
'Importance': model[-2].feature_importances_
}).sort_values(by='Importance', ascending=False)
else:
try:
feats = pd.DataFrame({
'Columns': X.columns,
'Importance': model.feature_importances_
}).sort_values(by='Importance', ascending=False)
except:
model.fit(X_train, y_train)
feats = pd.DataFrame({
'Columns': X.columns,
'Importance': model.feature_importances_
}).sort_values(by='Importance', ascending=False)
mod_scores = {}
try:
mod_scores['validation_score'] = val_scores.mean()
if return_folds:
mod_scores['fold_scores'] = val_scores
except:
mod_scores['validation_score'] = val_score
if return_test_score:
mod_scores['test_score'] = model.score(X_test, y_test)
if return_importances:
return mod_scores, feats
else:
return mod_scores我遇到的奇怪部分是，如果我在sklearn中创建一个管道，它可以在函数之外的dataset上工作，而不是在它的内部。例如：
from sklearn.pipeline import make_pipeline
from category_encoders import OrdinalEncoder
from xgboost import XGBClassifier
pipe = make_pipeline(OrdinalEncoder(), XGBClassifier())
X = df.drop('state', axis=1)
y = df['state']在这种情况下，pipe.fit(X, y)工作得很好。但是get_val_scores(pipe, X, y)在标题中的错误消息失败了。更奇怪的是，get_val_scores(pipe, X, y)似乎在处理其他数据集，比如泰坦尼克号。当模型在X_train和y_train上拟合时，就会产生误差。
在这种情况下，丢失函数是binary:logistic，而state列的值为successful和failed。
回答 4
Stack Overflow用户
回答已采纳
发布于 2021-04-24 10:51:57
目前，xgboost库正在更新以修复此错误，因此当前的解决方案是将库降级为旧版本，对于我来说，我已经通过将该库降级为xgboost v0.90来解决这个问题。
尝试通过cmd:检查xgboost版本
python
import xgboost
print(xgboost.__version__)
exit()如果版本不是0.90，那么通过：卸载当前版本
pip uninstall xgboost安装xgboost版本0.90
pip install xgboost==0.90再次运行您的代码！
Stack Overflow用户
发布于 2021-04-28 18:56:47
我在macOS Big上使用python3.8.6，只是在xgboost==1.4.0和1.4.1中遇到了这个错误。当我把评级降到1.3.3时，这个问题就消失了。尝试升级或降级取决于您的当前版本。
Stack Overflow用户
发布于 2021-04-30 16:54:19
此错误将在XGBoost 1.4.2中修复。
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/67095097
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