gpt4 book ai didi

python - xgboost: AttributeError: 'DMatrix' 对象没有属性 'handle'

转载 作者:太空狗 更新时间:2023-10-29 20:16:42 25 4
gpt4 key购买 nike

这个问题真的很奇怪,因为那部分与其他数据集工作得很好。

完整代码:

import numpy as np
import pandas as pd
import xgboost as xgb
from sklearn.cross_validation import train_test_split

# # Split the Learning Set
X_fit, X_eval, y_fit, y_eval= train_test_split(
train, target, test_size=0.2, random_state=1
)

clf = xgb.XGBClassifier(missing=np.nan, max_depth=6,
n_estimators=5, learning_rate=0.15,
subsample=1, colsample_bytree=0.9, seed=1400)

# fitting
clf.fit(X_fit, y_fit, early_stopping_rounds=50, eval_metric="logloss", eval_set=[(X_eval, y_eval)])
#print y_pred
y_pred= clf.predict_proba(test)[:,1]

最后一行导致以下错误(提供完整输出):

Will train until validation_0 error hasn't decreased in 50 rounds.
[0] validation_0-logloss:0.554366
[1] validation_0-logloss:0.451454
[2] validation_0-logloss:0.372142
[3] validation_0-logloss:0.309450
[4] validation_0-logloss:0.259002
Traceback (most recent call last):
File "../src/script.py", line 57, in
y_pred= clf.predict_proba(test)[:,1]
File "/opt/conda/lib/python3.4/site-packages/xgboost-0.4-py3.4.egg/xgboost/sklearn.py", line 435, in predict_proba
test_dmatrix = DMatrix(data, missing=self.missing)
File "/opt/conda/lib/python3.4/site-packages/xgboost-0.4-py3.4.egg/xgboost/core.py", line 220, in __init__
feature_types)
File "/opt/conda/lib/python3.4/site-packages/xgboost-0.4-py3.4.egg/xgboost/core.py", line 147, in _maybe_pandas_data
raise ValueError('DataFrame.dtypes for data must be int, float or bool')
ValueError: DataFrame.dtypes for data must be int, float or bool
Exception ignored in: >
Traceback (most recent call last):
File "/opt/conda/lib/python3.4/site-packages/xgboost-0.4-py3.4.egg/xgboost/core.py", line 289, in __del__
_check_call(_LIB.XGDMatrixFree(self.handle))
AttributeError: 'DMatrix' object has no attribute 'handle'

这里有什么问题?我不知道如何解决这个问题

UPD1:实际上这是 kaggle 问题:https://www.kaggle.com/insaff/bnp-paribas-cardif-claims-management/xgboost

最佳答案

这里的问题与初始数据有关:一些值是 float 或整数,一些是对象。这就是我们需要转换它们的原因:

from sklearn import preprocessing 
for f in train.columns:
if train[f].dtype=='object':
lbl = preprocessing.LabelEncoder()
lbl.fit(list(train[f].values))
train[f] = lbl.transform(list(train[f].values))

for f in test.columns:
if test[f].dtype=='object':
lbl = preprocessing.LabelEncoder()
lbl.fit(list(test[f].values))
test[f] = lbl.transform(list(test[f].values))

train.fillna((-999), inplace=True)
test.fillna((-999), inplace=True)

train=np.array(train)
test=np.array(test)
train = train.astype(float)
test = test.astype(float)

关于python - xgboost: AttributeError: 'DMatrix' 对象没有属性 'handle',我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/36065646/

25 4 0
Copyright 2021 - 2024 cfsdn All Rights Reserved 蜀ICP备2022000587号
广告合作:1813099741@qq.com 6ren.com