Question

我有一个列表＆＃34; simil＆＃34;，其中包含7个向量：

 > dput(simil)
structure(list(Monday = structure(c(0.889987253484581, 0.882957894295089, 
0.882232353177177, 0.874080268021168, 0.851760771472629, 0.811536071048775
), .Names = c("Sunday", "Tuesday", "Friday", "Wednesday", "Thursday", 
"Saturday")), Tuesday = structure(c(0.901682757072732, 0.882957894295089, 
0.874716806575548, 0.869202937572079, 0.855248496101086, 0.818659253763272
), .Names = c("Sunday", "Monday", "Wednesday", "Friday", "Thursday", 
"Saturday")), Wednesday = structure(c(0.88354911311872, 0.874716806575548, 
0.874080268021168, 0.853293126413937, 0.851921112754124, 0.841170795359615
), .Names = c("Sunday", "Tuesday", "Monday", "Friday", "Thursday", 
"Saturday")), Thursday = structure(c(0.86579834238668, 0.855248496101086, 
0.851921112754124, 0.851760771472629, 0.851384896045153, 0.836732564057725
), .Names = c("Sunday", "Tuesday", "Wednesday", "Monday", "Friday", 
"Saturday")), Friday = structure(c(0.882232353177177, 0.869202937572079, 
0.856441568566172, 0.853293126413937, 0.851384896045153, 0.80098779448239
), .Names = c("Monday", "Tuesday", "Sunday", "Wednesday", "Thursday", 
"Saturday")), Saturday = structure(c(0.866654844262859, 0.841170795359615, 
0.836732564057725, 0.818659253763272, 0.811536071048775, 0.80098779448239
), .Names = c("Sunday", "Wednesday", "Thursday", "Tuesday", "Monday", 
"Friday")), Sunday = structure(c(0.901682757072732, 0.889987253484581, 
0.88354911311872, 0.866654844262859, 0.86579834238668, 0.856441568566172
), .Names = c("Tuesday", "Monday", "Wednesday", "Saturday", "Thursday", 
"Friday"))), .Names = c("Monday", "Tuesday", "Wednesday", "Thursday", 
"Friday", "Saturday", "Sunday"), class = c("similMatrix", "list"
))

我现在想将它转换为dist对象，然后将其用于hclust（）。所以我使用as.dist（）并计算：

> as.dist(simil,diag = TRUE, upper = TRUE)
             Monday    Sunday   Tuesday    Friday Wednesday  Thursday  Saturday
Monday    0.0000000 0.8899873 0.8829579 0.8822324 0.8740803 0.8517608 0.8115361
Sunday    0.8899873 0.0000000 1.0000000 0.8692029 0.8747168 0.8552485 0.8186593
Tuesday   0.8829579 1.0000000 0.0000000 0.8532931 1.0000000 0.8519211 0.8411708
Friday    0.8822324 0.8692029 0.8532931 0.0000000 0.8519211 1.0000000 0.8367326
Wednesday 0.8740803 0.8747168 1.0000000 0.8519211 0.0000000 0.8513849 0.8009878
Thursday  0.8517608 0.8552485 0.8519211 1.0000000 0.8513849 0.0000000 1.0000000
Saturday  0.8115361 0.8186593 0.8411708 0.8367326 0.8009878 1.0000000 0.0000000

但这与我使用as.matrix（）时的结果略有不同：

> as.matrix(simil)
             Monday   Tuesday Wednesday  Thursday    Friday  Saturday    Sunday
Monday    1.0000000 0.8829579 0.8740803 0.8517608 0.8822324 0.8115361 0.8899873
Sunday    0.8899873 0.9016828 0.8835491 0.8657983 0.8564416 0.8666548 1.0000000
Tuesday   0.8829579 1.0000000 0.8747168 0.8552485 0.8692029 0.8186593 0.9016828
Friday    0.8822324 0.8692029 0.8532931 0.8513849 1.0000000 0.8009878 0.8564416
Wednesday 0.8740803 0.8747168 1.0000000 0.8519211 0.8532931 0.8411708 0.8835491
Thursday  0.8517608 0.8552485 0.8519211 1.0000000 0.8513849 0.8367326 0.8657983
Saturday  0.8115361 0.8186593 0.8411708 0.8367326 0.8009878 1.0000000 0.8666548

使用as.dist()时，矩阵不是完全对称的，有些对会出错，而as.matrix()则不会发生这种情况。这是为什么？我该如何纠正？

Answer 1

所以最后我设法通过首先转换为矩阵，然后交换行顺序，最后转换为dist对象来修复它：

simil = as.matrix(simil)
simil = simil[ c(1,3,5,6,4,7,2),]
simil = as.dist(1-simil,diag = TRUE, upper = TRUE)

> simil
              Monday    Tuesday  Wednesday   Thursday     Friday   Saturday     Sunday
Monday    0.00000000 0.11704211 0.12591973 0.14823923 0.11776765 0.18846393 0.11001275
Tuesday   0.11704211 0.00000000 0.12528319 0.14475150 0.13079706 0.18134075 0.09831724
Wednesday 0.12591973 0.12528319 0.00000000 0.14807889 0.14670687 0.15882920 0.11645089
Thursday  0.14823923 0.14475150 0.14807889 0.00000000 0.14861510 0.16326744 0.13420166
Friday    0.11776765 0.13079706 0.14670687 0.14861510 0.00000000 0.19901221 0.14355843
Saturday  0.18846393 0.18134075 0.15882920 0.16326744 0.19901221 0.00000000 0.13334516
Sunday    0.11001275 0.09831724 0.11645089 0.13420166 0.14355843 0.13334516 0.00000000

这可能是因为＆＃34; simil＆＃34;是从quanteda包的similarity（）函数创建的。

as.matrix（）和as.dist（）有不同的结果

1 个答案: