24 from daal
import step1Local, step2Master
25 from daal.algorithms.multinomial_naive_bayes
import prediction, training
26 from daal.algorithms
import classifier
27 from daal.data_management
import (
28 FileDataSource, DataSourceIface, NumericTableIface, HomogenNumericTable, MergedNumericTable
31 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
32 if utils_folder
not in sys.path:
33 sys.path.insert(0, utils_folder)
34 from utils
import printNumericTables
36 DAAL_PREFIX = os.path.join(
'..',
'data')
39 trainDatasetFileNames = [
40 os.path.join(DAAL_PREFIX,
'batch',
'naivebayes_train_dense.csv'),
41 os.path.join(DAAL_PREFIX,
'batch',
'naivebayes_train_dense.csv'),
42 os.path.join(DAAL_PREFIX,
'batch',
'naivebayes_train_dense.csv'),
43 os.path.join(DAAL_PREFIX,
'batch',
'naivebayes_train_dense.csv')
46 testDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'naivebayes_test_dense.csv')
53 predictionResult =
None
54 testGroundTruth =
None
60 masterAlgorithm = training.Distributed(step2Master, nClasses)
62 for i
in range(nBlocks):
64 trainDataSource = FileDataSource(
65 trainDatasetFileNames[i], DataSourceIface.notAllocateNumericTable,
66 DataSourceIface.doDictionaryFromContext
69 trainData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
70 trainGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
71 mergedData = MergedNumericTable(trainData, trainGroundTruth)
74 trainDataSource.loadDataBlock(mergedData)
77 localAlgorithm = training.Distributed(step1Local, nClasses)
80 localAlgorithm.input.set(classifier.training.data, trainData)
81 localAlgorithm.input.set(classifier.training.labels, trainGroundTruth)
85 masterAlgorithm.input.add(training.partialModels, localAlgorithm.compute())
88 masterAlgorithm.compute()
89 trainingResult = masterAlgorithm.finalizeCompute()
93 global predictionResult, testGroundTruth
96 testDataSource = FileDataSource(
97 testDatasetFileName, DataSourceIface.notAllocateNumericTable,
98 DataSourceIface.doDictionaryFromContext
102 testData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
103 testGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
104 mergedData = MergedNumericTable(testData, testGroundTruth)
107 testDataSource.loadDataBlock(mergedData)
110 algorithm = prediction.Batch(nClasses)
113 algorithm.input.setTable(classifier.prediction.data, testData)
114 algorithm.input.setModel(classifier.prediction.model, trainingResult.get(classifier.training.model))
117 predictionResult = algorithm.compute()
122 testGroundTruth, predictionResult.get(classifier.prediction.prediction),
123 "Ground truth",
"Classification results",
124 "NaiveBayes classification results (first 20 observations):", 20, flt64=
False
127 if __name__ ==
"__main__":