java - Very Simple K-means clustering example in ELKI -



java - Very Simple K-means clustering example in ELKI -

i'm trying utilize kmeans clustering functionality provided elki library.

this came with:

double[][] dblarray = new double[100][10] // 100 10-dimensional info points //populate array... kmeansinitialization<numbervector<double>> kinit = new firstkinitialmeans<>(); kmeanslloyd<numbervector<double>, doubledistance> kmeans = new kmeanslloyd<numbervector<double>, doubledistance>(euclideandistancefunction.static, k, kmeansmaxiter, kinit); databaseconnection dbc = new arrayadapterdatabaseconnection(dblarray)); database d = new staticarraydatabase(dbc, null); kmeans.run(d);

elki gives me:

de.lmu.ifi.dbs.elki.data.type.nosupporteddatatypeexception: no info type found satisfying: numbervector,field , numbervector available types: @ de.lmu.ifi.dbs.elki.database.abstractdatabase.getrelation(unknown source) @ de.lmu.ifi.dbs.elki.algorithm.abstractalgorithm.run(unknown source)

don't forget initialize database:

d.initialize();

at point, info fetched database connections, , indexes built.

if forget initialize database, remain empty.

java cluster-analysis elki

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