24 import daal.algorithms.kmeans.init
25 from daal.algorithms
import kmeans
27 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
28 if utils_folder
not in sys.path:
29 sys.path.insert(0, utils_folder)
30 from utils
import printNumericTable, createSparseTable
32 DAAL_PREFIX = os.path.join(
'..',
'data')
35 datasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'kmeans_csr.csv')
41 if __name__ ==
"__main__":
44 dataTable = createSparseTable(datasetFileName)
47 init = kmeans.init.Batch(nClusters, method=kmeans.init.randomDense)
49 init.input.set(kmeans.init.data, dataTable)
52 centroids = res.get(kmeans.init.centroids)
55 algorithm = kmeans.Batch(nClusters, nIterations, method=kmeans.lloydCSR)
57 algorithm.input.set(kmeans.data, dataTable)
58 algorithm.input.set(kmeans.inputCentroids, centroids)
60 res = algorithm.compute()
63 printNumericTable(res.get(kmeans.assignments),
"First 10 cluster assignments:", 10)
64 printNumericTable(res.get(kmeans.centroids),
"First 10 dimensions of centroids:", 20, 10)
65 printNumericTable(res.get(kmeans.objectiveFunction),
"Objective function value:")