47 from daal
import step1Local, step2Master
48 from daal.algorithms.multinomial_naive_bayes
import prediction, training
49 from daal.algorithms
import classifier
50 from daal.data_management
import (
51 FileDataSource, DataSourceIface, NumericTableIface, HomogenNumericTable, MergedNumericTable
54 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
55 if utils_folder
not in sys.path:
56 sys.path.insert(0, utils_folder)
57 from utils
import printNumericTables
59 DAAL_PREFIX = os.path.join(
'..',
'data')
62 trainDatasetFileNames = [
63 os.path.join(DAAL_PREFIX,
'batch',
'naivebayes_train_dense.csv'),
64 os.path.join(DAAL_PREFIX,
'batch',
'naivebayes_train_dense.csv'),
65 os.path.join(DAAL_PREFIX,
'batch',
'naivebayes_train_dense.csv'),
66 os.path.join(DAAL_PREFIX,
'batch',
'naivebayes_train_dense.csv')
69 testDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'naivebayes_test_dense.csv')
76 predictionResult =
None
77 testGroundTruth =
None
83 masterAlgorithm = training.Distributed(step2Master, nClasses)
85 for i
in range(nBlocks):
87 trainDataSource = FileDataSource(
88 trainDatasetFileNames[i], DataSourceIface.notAllocateNumericTable,
89 DataSourceIface.doDictionaryFromContext
92 trainData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
93 trainGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
94 mergedData = MergedNumericTable(trainData, trainGroundTruth)
97 trainDataSource.loadDataBlock(mergedData)
100 localAlgorithm = training.Distributed(step1Local, nClasses)
103 localAlgorithm.input.set(classifier.training.data, trainData)
104 localAlgorithm.input.set(classifier.training.labels, trainGroundTruth)
108 masterAlgorithm.input.add(training.partialModels, localAlgorithm.compute())
111 masterAlgorithm.compute()
112 trainingResult = masterAlgorithm.finalizeCompute()
116 global predictionResult, testGroundTruth
119 testDataSource = FileDataSource(
120 testDatasetFileName, DataSourceIface.notAllocateNumericTable,
121 DataSourceIface.doDictionaryFromContext
125 testData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
126 testGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
127 mergedData = MergedNumericTable(testData, testGroundTruth)
130 testDataSource.loadDataBlock(mergedData)
133 algorithm = prediction.Batch(nClasses)
136 algorithm.input.setTable(classifier.prediction.data, testData)
137 algorithm.input.setModel(classifier.prediction.model, trainingResult.get(classifier.training.model))
140 predictionResult = algorithm.compute()
145 testGroundTruth, predictionResult.get(classifier.prediction.prediction),
146 "Ground truth",
"Classification results",
147 "NaiveBayes classification results (first 20 observations):", 20, flt64=
False
150 if __name__ ==
"__main__":