January 2014
Beginner to intermediate
488 pages
8h 1m
Chinese
Content preview from R 錦囊妙計
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13.7 預測二元變數（羅吉斯迴歸）
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387
> plot(x ˜ factor(means), main="Original Clusters", xlab="Cluster Mean")
> plot(x ˜ factor(clust), main="Identified Clusters", xlab="Cluster Number")
如圖 13-3 所示的盒鬚圖。集群演算法完美地將資料分割為不重疊的組。原來的集群相互
重疊，而新界定的集群則不會相互重疊。
圖 13-3 集群比較圖
上列圖形使用一維資料，但是
dist
函數同樣適用於處理儲存在資料框架或矩陣的多維資
料。資料框架或矩陣中的每一列資料被視為多維空間中的一個觀測值，而
dist
函數計算
這些觀測值之間的距離。
延伸資訊
此範例是基於 R 軟體集群功能的基礎套件；尚有其他套件（如：
mclust
套件）能提供替
代的集群機制。
13.7 預測二元變數（羅吉斯迴歸）
問題點
您想要執行
羅吉斯迴歸
（
logistic regression
），即用來預測二元選擇事件發生機率的迴歸
模型。
388
|
第十三章
解決方案
使用
glm
函數，並設定
family=binomial
來執行羅吉斯迴歸。其輸出結果是個模型物
件：
> m <- glm(b ˜ x1 + x2 + ...
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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.