python-3.x - 在自定义类中使用 train_test_split 时出现类型错误(单例数组...)

Question

TypeError: Singleton array array(<__main__.AZHU_EmailClassifier_2object at 0x000001D6E7A680D0>, dtype=object) cannot be considered avalid collection.

当我尝试在我的自定义 AZHU_EmailClassifier_2 类中运行 train_test_split 函数时出现此错误。
我的课:

class AZHU_EmailClassifier_2:
    import os
    import numpy as np
    import pandas as pd
    from sklearn.model_selection import train_test_split

    def __init__(self):
        pass
    
    def retrain_model(self, csv_file):
        
        MIN_ROW_NUMBER = 500
        TEST_SIZE = 0.25
        RANDOM_STATE = 42
        
        self.os.chdir(r"c:\LORI\PROJECTS\ALLIANZ\INCOMING_CHANNELS") # <---- a retraining file mappaja
        
        df=self.pd.read_excel(csv_file,error_bad_lines=False, header=None)
        
        df.dropna(axis=0,how='any', inplace=True)
             
        rows_no=df.shape[0]
        if rows_no<MIN_ROW_NUMBER:
            print("Insufficient number of rows (<35.000)! RETRAINING ABORTED")
            return None

        X=df[0]
        y=df[1]
        
        X_train, X_test, y_train, y_test=self.train_test_split(X,y)
        #X_train, X_test, y_train, y_test=self.train_test_split(X,y,test_size=TEST_SIZE, random_state=RANDOM_STATE, stratify=y)
        
        return X_train
                

当我运行 train_test_split 函数时触发错误。
整个错误信息:

--------------------------------------------------------------------------- TypeError Traceback (most recent calllast) in 1 instance = AZHU_EmailClassifier_2()2----> 3 instance.retrain_model("retraining_dummy.xlsx")

in retrain_model(self, csv_file)28 y=df[1]29---> 30 X_train, X_test, y_train, y_test=self.train_test_split(X,y)31 #X_train, X_test, y_train, y_test=self.train_test_split(X,y,test_size=TEST_SIZE,random_state=RANDOM_STATE, stratify=y)32

~\Anaconda3\lib\site-packages\sklearn\model_selection_split.py intrain_test_split(*arrays, **options) 2125 raiseTypeError("Invalid parameters passed: %s" % str(options)) 2126-> 2127 arrays = indexable(*arrays) 2128 2129 n_samples = _num_samples(arrays[0])

~\Anaconda3\lib\site-packages\sklearn\utils\validation.py inindexable(*iterables)291 """292 result = [_make_indexable(X) for X in iterables]--> 293 check_consistent_length(*result)294 return result295

~\Anaconda3\lib\site-packages\sklearn\utils\validation.py incheck_consistent_length(*arrays)251 """252--> 253 lengths = [_num_samples(X) for X in arrays if X is not None]254 uniques = np.unique(lengths)255 if len(uniques) > 1:

~\Anaconda3\lib\site-packages\sklearn\utils\validation.py in(.0)251 """252--> 253 lengths = [_num_samples(X) for X in arrays if X is not None]254 uniques = np.unique(lengths)255 if len(uniques) > 1:

~\Anaconda3\lib\site-packages\sklearn\utils\validation.py in_num_samples(x)194 if hasattr(x, 'shape') and x.shape is not None:195 if len(x.shape) == 0:--> 196 raise TypeError("Singleton array %r cannot be considered"197 " a valid collection." % x)198 # Check that shape is returning an integer or default to len

TypeError: Singleton array array(<main.AZHU_EmailClassifier_2object at 0x000001D6E7A68F10>,dtype=object) cannot be considered a valid collection.

我不知道为什么它会抛出这个错误。你能指出我正确的方向吗？任何帮助表示赞赏!

Answer 1

您收到此错误是因为您导入了 train_test_split因此，在类内，train_test_split成为绑定(bind)方法而不是函数，并且每当调用该方法时，实例将作为第一个参数传递。这是可以重建情况的最小示例

class test():
    
    from sklearn.model_selection import train_test_split
    
    def retrain_model(self):
        print(self.train_test_split)
        print(self.train_test_split())
    
test_instance = test()
test_instance.retrain_model()

运行此脚本后，您将获得 TypeError

TypeError: Singleton array array(<__main__.test object at 0x7ffa473ae438>, dtype=object) cannot be considered a valid collection.

而 self.train_test_split 的位置内存中也是 0x7ffa473ae438 .
根据 PEP8

Imports are always put at the top of the file, just after any modulecomments and docstrings, and before module globals and constants.

因此，最简单的解决方案是导入类外的所有内容并调用 train_test_split。直接地

import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split

class AZHU_EmailClassifier_2():

    def __init__(self):
        pass
    
    def retrain_model(self,):
        
        MIN_ROW_NUMBER = 20
        TEST_SIZE = 0.25
        RANDOM_STATE = 42
                
        df = pd.DataFrame({0:np.linspace(1,100,100),1:np.random.rand(100)})
        X=df[0];y=df[1]
        X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=TEST_SIZE,random_state=RANDOM_STATE)
        
        return X_train

test = AZHU_EmailClassifier_2()
test.retrain_model()