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# Clustering results measurement

12 Jul 2011 (Updated )

Measure percentage of Accuracy and the Rand index of clustering results

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Description

Measure percentage of Accuracy and the Rand index of clustering results
The number of class must equal to the number cluster
Output
Acc = Accuracy of clustering results
rand_index = Rand's Index, measure an agreement of the clustering results
match = 2xk matrix which are the best match of the Target and clustering results
Input
T = 1xn target index
idx =1xn matrix of the clustering results

EX:
X=[randn(200,2);randn(200,2)+6,;[randn(200,1)+12,randn(200,1)]]; T=[ones(200,1);ones(200,1).*2;ones(200,1).*3];
idx=kmeans(X,3,'emptyaction','singleton','Replicates',5);
[Acc,rand_index,match]=AccMeasure(T,idx)

MATLAB release MATLAB 7 (R14)
MATLAB Search Path
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@roslan armina, replace Acc_measure with AccMeasure will work. It's my fault for the example code in the description. It's fixed now.

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@Pedro, thank you for pointing out. It's fixed now.

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08 May 2015 roslan armina

### roslan armina (view profile)

when i use your example, this error come out Undefined function or method 'Acc_measure' for input arguments of type 'double'.
how to solve it? thanks

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30 Jan 2014 Pedro

### Pedro (view profile)

there is a bug in your code since AccMeasure([1 1 1],[2 2 1]) and AccMeasure([2 2 2],[1 1 2]) give different accuracies

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