47 import daal.algorithms.kmeans.init
48 from daal.algorithms
import kmeans
50 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
51 if utils_folder
not in sys.path:
52 sys.path.insert(0, utils_folder)
53 from utils
import printNumericTable, createSparseTable
55 DAAL_PREFIX = os.path.join(
'..',
'data')
58 datasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'kmeans_csr.csv')
64 if __name__ ==
"__main__":
67 dataTable = createSparseTable(datasetFileName)
70 init = kmeans.init.Batch(nClusters, method=kmeans.init.randomDense)
72 init.input.set(kmeans.init.data, dataTable)
75 centroids = res.get(kmeans.init.centroids)
78 algorithm = kmeans.Batch(nClusters, nIterations, method=kmeans.lloydCSR)
80 algorithm.input.set(kmeans.data, dataTable)
81 algorithm.input.set(kmeans.inputCentroids, centroids)
83 res = algorithm.compute()
86 printNumericTable(res.get(kmeans.assignments),
"First 10 cluster assignments:", 10)
87 printNumericTable(res.get(kmeans.centroids),
"First 10 dimensions of centroids:", 20, 10)
88 printNumericTable(res.get(kmeans.objectiveFunction),
"Objective function value:")