machine learning - How WEKA compute Sum of Squared-Error Value or SSE? -


i new weka.

i know how weka sse value of simple k-means algorithm?

my friend , implemented java implemented k-means algorithm, , same dataset, our java implemented algorithm sse value of around 400 while weka around 2000. how possible?

my friend said weka uses k-means++. 1 of reasons make them have different result?

any idea appreciated. , please correct me if there's wrong. love learn.

have normalized data?

different normalization cause both different results , different sse values.

also try exporting result, , using same implementation compute both sse values.


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