Hi, all,
I'd like to do the clustering analysis in my dataset. The example data are as
follows:
Dataset 1:
500, 490, 486, 490, 491, 493, 480, 461, 504, 476, 434, 500, 470, 495, 3116,
3142, 12836, 3062, 3091, 3141, 3177, 3150, 3114, 3149;
Dataset 2:
506, 473, 495, 494, 434, 459, 445, 475, 476, 128367, 470, 513, 466, 476,482,
1201, 469, 502;
I had so many datasets like that. Basically, every dataset can classify one or
two clusters (no more than 2), meanwhile, there have error data points, for
example, 12836 is error data point in Dataset 1; and 128367, 1201 is error data
points in dataset2.
The clustered data is following the normal distribution, the standard deviation
was known. ThatÂ’s mean the one cluster is following the normal distribution
when the dataset classified one cluster like dataset2; the two clusters are
following the normal distribution respectively when the dataset classified two
clusters like dataset1. Error data are far away of the mean.
I am wondering is there any mathematic pipeline/function can do the
analysis that removing error data, and clustering the dataset in 1 or 2
clusters?
Thank you for your reply.
2009-03-27
wanggd1983
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