做关联分析前数据预处理的问题

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各位大神们，小弟R语言 初学者 在做AR的时候遇到了个问题，想请教下各位。比如我手上有的数据中部分如下

Automotive	Computers	Personal Electronics	Garden	Clothing	Health	Jewelry	Housewares
0	0	0	1	0	0	0	1
1	0	1	1	0	1	0	0
1	1	0	0	0	0	0	1

第一行是项目，下面1代表购买，0代表没有购买，我想要根据这个数据导入R 中做关联分析，可是直接用read.transactions导入的话数据没法做分析会出现以下问题我是需要先把0-1型的数据变成character型的吗？怎么变呢？ 在线求，请大神们帮帮我。。。

1. > catalog<- read.transactions("CatalogCrossSell.csv")
   
2. > summary(catalog)
   
3. transactions as itemMatrix in sparse format with
   
4. 201 rows (elements/itemsets/transactions) and
   
5. 88 columns (items) and a density of 0.01142017
   
6. 
   
7. most frequent items:
   
8. 1,1,1,0,0,1,0,0, 1,1,1,0,0,0,0,1, 0,0,0,1,0,1,0,1, 1,0,0,0,0,1,0,0, 1,1,1,0,0,1,0,1,          (Other)
   
9.               16                9                7                7                7              156
   
10. 
    
11. element (itemset/transaction) length distribution:
    
12. sizes
    
13.   1   2
    
14. 200   1
    
15. 
    
16.    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
    
17.   1.000   1.000   1.000   1.005   1.000   2.000
    
18. 
    
19. includes extended item information - examples:
    
20.             labels
    
21. 1 0,0,0,0,0,1,0,0,
    
22. 2 0,0,0,0,1,0,1,0,
    
23. 3 0,0,0,0,1,0,1,1,

复制代码

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关键词：数据预处理 关联分析 预处理 Transactions distribution Automotive Health 初学者 项目

不好意思 代码没显示出来。。

1. > catalog<- read.transactions("CatalogCrossSell.csv")
   
2. > summary(catalog)
   
3. transactions as itemMatrix in sparse format with
   
4. 201 rows (elements/itemsets/transactions) and
   
5. 88 columns (items) and a density of 0.01142017
   
6. 
   
7. most frequent items:
   
8. 1,1,1,0,0,1,0,0, 1,1,1,0,0,0,0,1, 0,0,0,1,0,1,0,1, 1,0,0,0,0,1,0,0, 1,1,1,0,0,1,0,1,          (Other)
   
9.               16                9                7                7                7              156
   
10. 
    
11. element (itemset/transaction) length distribution:
    
12. sizes
    
13.   1   2
    
14. 200   1
    
15. 
    
16.    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
    
17.   1.000   1.000   1.000   1.005   1.000   2.000
    
18. 
    
19. includes extended item information - examples:
    
20.             labels
    
21. 1 0,0,0,0,0,1,0,0,
    
22. 2 0,0,0,0,1,0,1,0,
    
23. 3 0,0,0,0,1,0,1,1,
    
24. > str(catalog)
    
25. Formal class 'transactions' [package "arules"] with 3 slots
    
26.   ..@ data       :Formal class 'ngCMatrix' [package "Matrix"] with 5 slots
    
27.   .. .. ..@ i       : int [1:202] 86 87 7 56 60 54 40 10 69 66 ...
    
28.   .. .. ..@ p       : int [1:202] 0 2 3 4 5 6 7 8 9 10 ...
    
29.   .. .. ..@ Dim     : int [1:2] 88 201
    
30.   .. .. ..@ Dimnames:List of 2
    
31.   .. .. .. ..$ : NULL
    
32.   .. .. .. ..$ : NULL
    
33.   .. .. ..@ factors : list()
    
34.   ..@ itemInfo   :'data.frame':        88 obs. of  1 variable:
    
35.   .. ..$ labels: chr [1:88] "0,0,0,0,0,1,0,0," "0,0,0,0,1,0,1,0," "0,0,0,0,1,0,1,1," "0,0,0,0,1,1,0,1," ...
    
36.   ..@ itemsetInfo:'data.frame':        0 obs. of  0 variables

复制代码

不好意思，代码没显示出来，这里补上

> catalog<- read.transactions("CatalogCrossSell.csv")
> summary(catalog)
transactions as itemMatrix in sparse format with
201 rows (elements/itemsets/transactions) and
88 columns (items) and a density of 0.01142017

most frequent items:
1,1,1,0,0,1,0,0, 1,1,1,0,0,0,0,1, 0,0,0,1,0,1,0,1, 1,0,0,0,0,1,0,0, 1,1,1,0,0,1,0,1,          (Other)
              16                9                7                7                7              156

element (itemset/transaction) length distribution:
sizes
  1   2
200   1

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
  1.000   1.000   1.000   1.005   1.000   2.000

includes extended item information - examples:
            labels
1 0,0,0,0,0,1,0,0,
2 0,0,0,0,1,0,1,0,
3 0,0,0,0,1,0,1,1,
> str(catalog)
Formal class 'transactions' [package "arules"] with 3 slots
  ..@ data       :Formal class 'ngCMatrix' [package "Matrix"] with 5 slots
  .. .. ..@ i       : int [1:202] 86 87 7 56 60 54 40 10 69 66 ...
  .. .. ..@ p       : int [1:202] 0 2 3 4 5 6 7 8 9 10 ...
  .. .. ..@ Dim     : int [1:2] 88 201
  .. .. ..@ Dimnames:List of 2
  .. .. .. ..$ : NULL
  .. .. .. ..$ : NULL
  .. .. ..@ factors : list()
  ..@ itemInfo   :'data.frame':        88 obs. of  1 variable:
  .. ..$ labels: chr [1:88] "0,0,0,0,0,1,0,0," "0,0,0,0,1,0,1,0," "0,0,0,0,1,0,1,1," "0,0,0,0,1,1,0,1," ...
  ..@ itemsetInfo:'data.frame':        0 obs. of  0 variables

不好意思 代码没显示出来 ，这里补上

> catalog<- read.transactions("CatalogCrossSell.csv")
> summary(catalog)
transactions as itemMatrix in sparse format with
201 rows (elements/itemsets/transactions) and
88 columns (items) and a density of 0.01142017

most frequent items:
1,1,1,0,0,1,0,0, 1,1,1,0,0,0,0,1, 0,0,0,1,0,1,0,1, 1,0,0,0,0,1,0,0, 1,1,1,0,0,1,0,1,          (Other)
              16                9                7                7                7              156

element (itemset/transaction) length distribution:
sizes
  1   2
200   1

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
  1.000   1.000   1.000   1.005   1.000   2.000

includes extended item information - examples:
            labels
1 0,0,0,0,0,1,0,0,
2 0,0,0,0,1,0,1,0,
3 0,0,0,0,1,0,1,1,
> str(catalog)
Formal class 'transactions' [package "arules"] with 3 slots
  ..@ data       :Formal class 'ngCMatrix' [package "Matrix"] with 5 slots
  .. .. ..@ i       : int [1:202] 86 87 7 56 60 54 40 10 69 66 ...
  .. .. ..@ p       : int [1:202] 0 2 3 4 5 6 7 8 9 10 ...
  .. .. ..@ Dim     : int [1:2] 88 201
  .. .. ..@ Dimnames:List of 2
  .. .. .. ..$ : NULL
  .. .. .. ..$ : NULL
  .. .. ..@ factors : list()
  ..@ itemInfo   :'data.frame':        88 obs. of  1 variable:
  .. ..$ labels: chr [1:88] "0,0,0,0,0,1,0,0," "0,0,0,0,1,0,1,0," "0,0,0,0,1,0,1,1," "0,0,0,0,1,1,0,1," ...
  ..@ itemsetInfo:'data.frame':        0 obs. of  0 variables

不好意思 代码没显示出来 ，这里补上

> catalog<- read.transactions("CatalogCrossSell.csv")
> summary(catalog)
transactions as itemMatrix in sparse format with
201 rows (elements/itemsets/transactions) and
88 columns (items) and a density of 0.01142017

most frequent items:
1,1,1,0,0,1,0,0, 1,1,1,0,0,0,0,1, 0,0,0,1,0,1,0,1, 1,0,0,0,0,1,0,0, 1,1,1,0,0,1,0,1,          (Other)
              16                9                7                7                7              156

element (itemset/transaction) length distribution:
sizes
  1   2
200   1

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
  1.000   1.000   1.000   1.005   1.000   2.000

includes extended item information - examples:
            labels
1 0,0,0,0,0,1,0,0,
2 0,0,0,0,1,0,1,0,
3 0,0,0,0,1,0,1,1,
> str(catalog)
Formal class 'transactions' [package "arules"] with 3 slots
  ..@ data       :Formal class 'ngCMatrix' [package "Matrix"] with 5 slots
  .. .. ..@ i       : int [1:202] 86 87 7 56 60 54 40 10 69 66 ...
  .. .. ..@ p       : int [1:202] 0 2 3 4 5 6 7 8 9 10 ...
  .. .. ..@ Dim     : int [1:2] 88 201
  .. .. ..@ Dimnames:List of 2
  .. .. .. ..$ : NULL
  .. .. .. ..$ : NULL
  .. .. ..@ factors : list()
  ..@ itemInfo   :'data.frame':        88 obs. of  1 variable:
  .. ..$ labels: chr [1:88] "0,0,0,0,0,1,0,0," "0,0,0,0,1,0,1,0," "0,0,0,0,1,0,1,1," "0,0,0,0,1,1,0,1," ...
  ..@ itemsetInfo:'data.frame':        0 obs. of  0 variables