22 from daal.algorithms.adaboost
import prediction, training
23 from daal.algorithms
import classifier
24 from daal.data_management
import (
25 FileDataSource, DataSourceIface, HomogenNumericTable, MergedNumericTable, NumericTableIface
28 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
29 if utils_folder
not in sys.path:
30 sys.path.insert(0, utils_folder)
31 from utils
import printNumericTables
33 DAAL_PREFIX = os.path.join(
'..',
'data')
36 trainDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'adaboost_train.csv')
38 testDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'adaboost_test.csv')
43 predictionResult =
None
44 testGroundTruth =
None
51 trainDataSource = FileDataSource(
52 trainDatasetFileName, DataSourceIface.notAllocateNumericTable,
53 DataSourceIface.doDictionaryFromContext
57 trainData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
58 trainGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
59 mergedData = MergedNumericTable(trainData, trainGroundTruth)
62 trainDataSource.loadDataBlock(mergedData)
65 algorithm = training.Batch()
68 algorithm.input.set(classifier.training.data, trainData)
69 algorithm.input.set(classifier.training.labels, trainGroundTruth)
72 trainingResult = algorithm.compute()
76 global predictionResult, testGroundTruth
79 testDataSource = FileDataSource(
80 testDatasetFileName, DataSourceIface.notAllocateNumericTable,
81 DataSourceIface.doDictionaryFromContext
85 testData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
86 testGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
87 mergedData = MergedNumericTable(testData, testGroundTruth)
90 testDataSource.loadDataBlock(mergedData)
93 algorithm = prediction.Batch()
96 algorithm.input.setTable(classifier.prediction.data, testData)
97 algorithm.input.setModel(classifier.prediction.model, trainingResult.get(classifier.training.model))
101 predictionResult = algorithm.compute()
105 testGroundTruth, predictionResult.get(classifier.prediction.prediction),
106 "Ground truth",
"Classification results",
107 "AdaBoost classification results (first 20 observations):", 20, flt64=
False
110 if __name__ ==
"__main__":