AttributeError:将混淆矩阵转换为数据帧时，“”H2OFrame“”对象没有属性“”lower“”

Question

我正在尝试将混淆矩阵转换为python 2D列表，这样我就可以访问组件。

我在尝试将混淆矩阵转换为数据帧时遇到错误。

import h2o
from h2o.estimators.gbm import H2OGradientBoostingEstimator
import pandas as pd

h2o.init()

training_file = "AirlinesTrain.csv"
train = h2o.import_file(training_file)
response_col = "IsDepDelayed"
distribution = "multinomial"
project_name = "airlines"
problem_type = "binary-classification"
predictors = train.columns
gbm = H2OGradientBoostingEstimator(nfolds=3,
                                    distribution=distribution)
gbm.train(x=predictors,
           y=response_col,
           training_frame=train)
print("gbm.confusion_matrix(train).as_data_frame()")
print(gbm.confusion_matrix(train).as_data_frame())#This errors AttributeError: 'H2OFrame' object has no attribute 'lower'

注意:如果我使用cars数据集，则不会出现错误：

cars = h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/junit/cars_20mpg.csv")
cars["cylinders"] = cars["cylinders"].asfactor()
#r = cars[0].runif()
#train = cars[r > .2]
#valid = cars[r <= .2]
train=cars
response_col = "cylinders"
distribution = "multinomial"
predictors = ["displacement","power","weight","acceleration","year"]

Answer 1

遇到了同样的问题。文档中可能有错误，因为它提到您可以传递一个H2OFrame。https://docs.h2o.ai/h2o/latest-stable/h2o-docs/performance-and-prediction.html

但是，我认为如果你通过了train=True，它就可以工作了

print(gbm.confusion_matrix(train=True).as_data_frame())