0
を見ずに多数決に従ってNbClust（）から最適なクラスタ数を取得rは：</p> <pre><code>nc <- NbClust(df, distance="euclidean", min.nc=2, max.nc=10, method="complete") </code></pre> <p>と私のコンソールに次のような出力が得られます：私は一次元データに<code>NbClust()</code>を実行しているコンソール
[1] "Frey index : No clustering structure in this data set"
*** : The Hubert index is a graphical method of determining the number of clusters.
In the plot of Hubert index, we seek a significant knee that corresponds to a
significant increase of the value of the measure i.e the significant peak in Hubert
index second differences plot.
*** : The D index is a graphical method of determining the number of clusters.
In the plot of D index, we seek a significant knee (the significant peak in Dindex
second differences plot) that corresponds to a significant increase of the value of
the measure.
*******************************************************************
* Among all indices:
* 1 proposed 4 as the best number of clusters
* 1 proposed 8 as the best number of clusters
* 2 proposed 9 as the best number of clusters
* 2 proposed 10 as the best number of clusters
***** Conclusion *****
* According to the majority rule, the best number of clusters is 9
*******************************************************************
私はそれを見ずに（上記の出力の最後の行で）値「9」を取得できますか？
ありがとうございました！次のように
正規化されたデータが見えます：zx8754へ
df <- structure(list(V1 = c(-0.142196220923589, 4.3271395706369, 5.00420146139183,
-0.292948282536991, -0.292948282536991, -0.292948282536991, -0.191455118249021,
-0.292948282536991, -0.292948282536991, -0.292948282536991, 1.04365387777657,
0.150712390018241, -0.275757257967042, -0.292948282536991, -0.292948282536991,
0.00392748792098075, -0.0235120320656692, 0.150712390018241,
-0.292948282536991, 0.22278245456149, -0.292948282536991, -0.292948282536991,
0.0888908208916921, -0.292948282536991, -0.269806518692829, -0.292948282536991,
-0.292948282536991, -0.292948282536991, -0.292948282536991, -0.287328139889123,
-0.030454561218918, 0.25980927671215, -0.292948282536991, -0.223192394378158,
-0.292948282536991, -0.292948282536991, -0.292948282536991, 0.0657490570475295,
-0.292948282536991, -0.292948282536991, -0.292948282536991, -0.215258075345874,
0.0862460478809306, 0.0862460478809306, -0.522051744594201, -0.518084585078059,
-0.496595804365622, -0.522051744594201, -0.516431601946333, -0.518084585078059
)), .Names = "V1", row.names = c(NA, -50L), class = "data.frame")