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I'm using function cvKMeans2() from OpenCV library for clustering. It has optional parametr:
centers - The optional output array of the cluster centers
The same parametr is also in function kmeans().
I want to know informations about clusters. But I haven't found what is a type of that cluster center in array, so I can't get it.
Thanks for any advices!
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Introducing k-Means The "cluster center" is the arithmetic mean of all the points belonging to the cluster. Each point is closer to its own cluster center than to other cluster centers.
To calculate the centroid from the cluster table just get the position of all points of a single cluster, sum them up and divide by the number of points.
k-means is the most widely-used centroid-based clustering algorithm. Centroid-based algorithms are efficient but sensitive to initial conditions and outliers. This course focuses on k-means because it is an efficient, effective, and simple clustering algorithm. Figure 1: Example of centroid-based clustering.
Clusters are identified by applying a mathematical algorithm that assigns vertices (i.e., users) to subgroups of relatively more connected groups of vertices in the network. The Clauset-Newman-Moore algorithm [8], used in NodeXL, enables you to analyze large network datasets to efficiently find subgroups.
In OpenCV 2.0, the equivalent kmeans function takes a CV_32FC1 matrix, but OpenCV 2.0 is quite a substantial upgrade to the old kmeans2 function, so I cannot be sure if the cluster centers datatype would still be the same for the OpenCV 1.1 version.
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This makes it look like the "centers" parameter has the same type as the first parameter, which other documentation says:
The metatype CvArr is used only as a function parameter to specify that the function accepts arrays of multiple types, such as IplImage*, CvMat* or even CvSeq* sometimes. The particular array type is determined at runtime by analyzing the first 4 bytes of the header.
That, combined with this question, makes me think you should try passing a CV array (vector) to get the centers.
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