군집 알고리즘을 적용하는 데 어려운 점 하나는 알고리즘이 잘 작동하는지 평가하거나 여러 알
고리즘의 출력을 비교하기가 매우 어렵다는 것입니다. 군집 알고리즘의 평가에 대해 이야기한
후 실제 데이터셋을 이용해
k
-평균, 병합 군집,
DBSCAN
알고리즘을 비교해보겠습니다.
타깃값으로 군집 평가하기
군집 알고리즘의 결과를 실제 정답 클러스터와 비교하여 평가할 수 있는 지표들이 있습니
다.
1
(최적일 때)과
0
(무작위로 분류될 때) 사이의 값을 제공하는
ARI
adjusted
rand
index
40
와
NMI
normalized
mutual
information
41
가 가장 ...
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