在sklearn中进行测试和训练数据拆分错误

Question

我正在尝试通过"train_test_split“来划分测试和训练数据。为什么我得到错误“至少需要一个数组作为输入”。

"train_test_split“的输入可以是数组和dataFrame，对吗？

import pandas as pd
import numpy as np 
from rpy2.robjects.packages import importr
import rpy2.robjects as ro
import pandas.rpy.common as rpy_common 
from sklearn.model_selection import  train_test_split

def la():
 ro.r('library(MASS)')
 pydf = rpy_common.load_data(name = 'Boston', package=None, convert=True)
 pddf = pd.DataFrame(pydf)
 targetIndex = pddf.columns.get_loc("medv") 

 # make train and test data
rowNum = pddf.shape[0]  
colNum = pddf.shape[1]
print(type(pddf.as_matrix()))
print(pddf.as_matrix().shape)
m = np.asarray(pddf.as_matrix()).reshape(rowNum,colNum)
print(type(m))
x_train, x_test, y_train, y_test = train_test_split(x = m[:, 0:rowNum-2], \
                                                    y = m[:, -1],\
                                                    test_size = 0.5) 
# error:     raise ValueError("At least one array required as input")
ValueError: At least one array required as input

Answer 1

在sklearn docs中，使用位置项解包("*args")来处理数组。

您正在使用关键字参数"x=“和"y="，它试图通过查看"x”和"y“是否是特殊关键字选项的名称来处理这些参数。

尝试：

train_test_split(m[:, 0:rowNum-2], m[:, -1], test_size=0.5)

(从数组中删除关键字参数名称)。