Flow
weka.SimpleKMeans_EuclideanDistance

weka.SimpleKMeans_EuclideanDistance

Visibility: public Uploaded 03-06-2014 by Joaquin Vanschoren Weka_3.7.10 0 runs
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
D. Arthur, S. Vassilvitskii: k-means++: the advantages of carefull seeding. In: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, 1027-1035, 2007.

Components

Aweka.EuclideanDistance(1)Distance function to use. (default: weka.core.EuclideanDistance)

Parameters

ADistance function to use. (default: weka.core.EuclideanDistance)default: weka.core.EuclideanDistance
IMaximum number of iterations.default: 500
MDon't replace missing values with mean/mode.
Nnumber of clusters. (default 2).default: 2
OPreserve order of instances.
PInitialize using the k-means++ method.
SRandom number seed. (default 10)default: 10
VDisplay std. deviations for centroids.
fastEnables faster distance calculations, using cut-off values. Disables the calculation/output of squared errors/distances.
num-slotsNumber of execution slots. (default 1 - i.e. no parallelism)default: 1

0
Runs

List all runs
Parameter:
Rendering chart
Rendering table