Python中的KMeans：ValueError：使用序列设置数组元素

Question

我正在尝试使用 numpy 和 sklearn 在 Python 中执行 kmeans 聚类。 我有一个包含 45 列和 645 行的 txt 文件。第一行是 Y，其余 644 行是 X。

我的 Python 代码是：

import numpy as np
import matplotlib.pyplot as plt
import csv

from sklearn.cluster import KMeans

#The following code reads the first row and terminates the loop
with open('trainDataXY.txt','r') as f:
   read = csv.reader(f)
   for first_row in read:
        y = list(first_row)
        break

#The following code skips the first row and reads rest of the rows
firstLine = True
with open('trainDataXY.txt','r') as f1:
    readY = csv.reader(f1)
    for rows in readY:
         if firstLine:
              firstLine=False
              continue
         x = list(readY)

X = np.array((x,y), dtype=object)
kmean = KMeans(n_clusters=2)
kmean.fit(X)

我在这一行遇到错误：kmean.fit(X)

我得到的错误是：

Traceback (most recent call last):
File "D:\file_path\kmeans.py", line 25, in <module> kmean.fit(X)
File "C:\Anaconda2\lib\site-packages\sklearn\cluster\k_means_.py",
line 812, in fit X = self._check_fit_data(X)
File "C:\Anaconda2\lib\site-packages\sklearn\cluster\k_means_.py",
line 786, in _check_fit_data X = check_array(X, accept_sparse='csr',
dtype=np.float64)
File "C:\Anaconda2\lib\site-packages\sklearn\utils\validation.py",
line 373, in check_array array = np.array(array, dtype=dtype,
order=order, copy=copy) ValueError: setting an array element with a
sequence.`

trainDataXY.txt

1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3 ,3,3,3,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5 47,64,508,1116,1116,1116,1116,11161610101161011610101161615,1161010101015101515,11616151015151515,11615

47,65,42 ,11,1116,116,1116,116,1116,1116,1116.116,111.11.111161011618,111.116015,1165,201015,116515,1165.11151015,1165.11515,1165.1115,1165

49,205,205,111110108,1111101010110110101011010110108,1115.11011010105105,115.1115,11510510451051085.11151051085.5855.11151510815.1175

51,78,52,46,56,74,50,28,38,38,39,38,38,37,40,39,39,41,96,101,99,104,97,101,111,101,104,115,116,116,119,110,112,119,116,116,135,130,129,135,120,108,133,120,125 P>

55,79,53,65,52,102,55,28,36,39,40,38,39,37,40,39,40,42,79,86,84,105,84,57,110,85,76,117,118,115,110 ,66,86,117,117,118,123,130,130,129,106,93,130,113,114

48,80,59,81,50,120,63,26,31,39,40,39,40,38,42,37,41,42,53,73,77,90,47,34,76 ,52,63,106,102,97,80,33,68,105,105,113,115,130,124,111,83,91,128,105,110

45,95,56,86,38,137,60,27,27,39,40,38,40,37,41,52,38,41,24,44,44,79,40,32,48 ,26,28,63,52,59,42,30,62,79,67,77,116,121,122,114,96,90,126,93,103

45,93,47,86,35,144,60,26,27,39,40,45,39,38,43,87,46,58,33,21,26,62,42,49,49 ,37,24,33,41,56,29,28,68,79,58,74,115,111,115,119,117,104,132,92,97

48,85,50,83,37,142,62,25,29,57,47,77,43,64,61,115,70,101,41,28,28,48,39,46,42,38,37 ,47,43,74,32,28,64,86,80,81,127,113,99,130​​,140,​​112,139,92,97

48,94,78,77,30,138,57,28,29,91,66,94,61,94,103,129,89,140,​​38,34,32,38,33,43,38,36,39,50 ,39,75,31,33,65,89,82,84,127,112,100,133,141,107,136,95,97

45,108,158,77,30,140,​​67,29,26,104,97,113,92,106,141,137,116,151,33,32,32,43,44,40,37,34,37,54,86,77,55,48,77,112,1313,109,125,120, ,98,129,89,99

48,115,250105,115010101010101501501551551581555,1155.11851855.115515855.11551585.1155.11515855.1155

131,157,111111111111111111111111111111111111111111111181181851818158185.1188185.1188185.111815815

160,160,1111,1111111111161165,1111111111111111111111115115.1111511511511510115115.1115.111511511511511515115115115115115115115.11165.1116151151151151151151165.1115151151151151165.11151151151165.11165.11165.1115115.111615

Answer 1

您的数据矩阵不应该是object 类型。它应该是一个形状为n_samples x n_features的数字矩阵。

当人们试图将样本列表转换为数据矩阵时，通常会出现此错误，并且每个样本都是数组或列表，并且至少有一个样本的长度与其他样本的长度不同。这可以通过评估np.unique(list(map(len, X))) 来解决。

在你的情况下是不同的。确保获得数据矩阵。首先要尝试将X = np.array((x,y), dtype=object) 行替换为创建数据矩阵的内容。

您还应该选择使用numpy.recfromcsv 来读取您的数据。这将使所有内容更易于阅读。