November 2020
Intermediate to advanced
396 pages
8h 34m
Japanese
book
データサイエンスのための統計学入門 第2版 ―予測、分類、統計モデリング、統計的機械学習とR/Pythonプログラミング
by Peter Bruce, Andrew Bruce, Peter Gedeck, 黒川 利明, 大橋 真也
Content preview from データサイエンスのための統計学入門 第2版 ―予測、分類、統計モデリング、統計的機械学習とR/Pythonプログラミング
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7.3
階層クラスタリング
■
323
k
平均とは対照的に、前もってクラスタの個数を指定する必要はない。
R
では、クラ
スタの個数を抽出するには
cutree
関数を使うことができる。
（
R
）
cutree(hcl, k=4)
GOOGL AMZN AAPL MSFT CSCO INTC CVX XOM SLB COP JPM WFC
1 2 3 3 3 3 4 4 4 4 3 3
USB AXP WMT TGT HD COST
3 3 3 3 3 3
Python
では
fcluster
関数を使い、同じことができる。
（
Python
）
memb = fcluster(Z, 4, criterion='maxclust')
memb = pd.Series(memb, index=df.index)
for key, item in memb.groupby(memb):
print(f"{key} : {', '.join(item.index)}")
抽出クラスタ数は
4
に設定され、
Google
と
Amazon
はそれだけのクラスタになる。
石油株はすべて別のクラスタになる。残りの株式は、
4
番目のクラスタになる。
7.3.3
凝集アルゴリズム
階層クラスタリングの主なアルゴリズムは、反復的に類似クラスタを併合する凝集ア
ルゴリズムだ。凝集アルゴリズムは、
1
レコードクラスタを形成するレコードから開始
して、順次、より大きなクラスタになる。第
1
ステップでは、レコードのすべての対距
離を計算する。
レコードの各対
(
x
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.