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K means question

Hey everybody,

I'm currently in the process of clustering a set of points into different sections. Though, the k means algorithm requires me to explicitly set the number of clusters to divide the set of points in. Is there an alternative algorithm, where I can pass in a set of points and a maximum distance, which divides point clusters from each other? What I would like to have returned is a list of clusters of yet unknown size, containing a sub-set of points.

I would be very thankful for any directions.

Thanks, Marcel

K means question

Hey everybody,

I'm currently in the process of clustering a set of points into different sections. Though, the k means algorithm requires me to explicitly set the number of clusters to divide the set of points in. Is there an alternative algorithm, where I can pass in a set of points and a maximum distance, which divides point clusters from each other? What I would like to have returned is a list of clusters of yet unknown size, containing a sub-set of points.

I would be very thankful for any directions.

Thanks, Marcel

K means question

Hey everybody,

I'm currently in the process of clustering a set of points into different sections. Though, the k means algorithm requires me to explicitly set the number of clusters to divide the set of points in. Is there an alternative algorithm, where I can pass in a set of points and a maximum distance, which divides point clusters from each other? What I would like to have returned is a list of clusters of yet unknown size, containing a sub-set of points.

I would be very thankful for any directions.

Thanks, Marcel