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精通機器學習
book

精通機器學習

by Aurélien Géron
April 2020
Intermediate to advanced
816 pages
18h 32m
Chinese
GoTop Information, Inc.
Content preview from 精通機器學習
高斯混合
|
259
"spherical"
所有群聚都必須是球形的
但它們的直徑可為任意值
也就是有不同的變異度
)。
"diag"
群聚可以是任何大小的任何橢圓形
但是橢圓的軸必須與座標軸平行
也就是共變異
數矩陣必須是對角的
)。
"tied"
所有群聚必須是同一種橢圓形
有相同的大小與方向
也就是所有群聚的共變異數矩
陣都是一樣的
)。
covariance_type
的預設值是
"full"
代表各個群聚都可以是任何形狀
大小與方向
有它自己的無限制共變異數矩陣
)。
9-18
EM
演算法在
covariance_type
設為
"tied"
"spherical」
時找到的解
9-18 tied
群聚
spherical
群聚
的高斯混合
訓練
GaussianMixture
模型的計算複雜度與實例數量
m
維數
n
群聚數
k
以及共變異數矩陣的限制有關
如果
covariance_type
"spherical"
"diag"
它是
O(kmn)
假設資料有群聚結構
如果
covariance_type
"tied"
"full"
它是
O
(
kmn
2
+
kn
3
)
所以難以處理大量的特徵
高斯混合模型也可以進行異常檢測
我們來看一下怎麼做
260
|
第九章:無監督學習技術
使用高斯混合進行異常檢測
異常檢測
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Publisher Resources

ISBN: 9789865024345