January 2014
Beginner to intermediate
860 pages
20h 37m
Japanese
Content preview from Rクイックリファレンス 第2版
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574
21 章 分類モデル
Length Class Mode
formula 3 formula call
trees 100 -none- list
votes 6440 -none- numeric
class 3220 -none- character
samples 322000 -none- numeric
importance 57 -none- numeric
> table(actual=spambase.training$is_spam,
+ predicted=predict(spam.bag, newdata=spambase.training)$class)
predicted
actual 0 1
0 1878 73
1 344 925
> table(actual=spambase.validation$is_spam,
+ predicted=predict(spam.bag, newdata=spambase.validation)$class)
predicted
actual 0 1
0 804 33
1 162 382
ipred
ライブラリの
bagging
関数も試せます。この関数は、「
20.7.1.3
回帰のため
のバギング」で使用しています。
21.2.2.2
ブースティング
ada
パッケージの
ada
関数を使うと、分類のためのブースティングモデルを構築で
きます（この関数は回帰問題には使えません）。
##
デフォルト
S3
メソッド：
ada(x, y,test.x, test.y=NULL, ...
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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.