24 from daal.algorithms.adaboost
import prediction, training
25 from daal.algorithms
import classifier
26 from daal.data_management
import (
27 FileDataSource, DataSourceIface, HomogenNumericTable, MergedNumericTable, NumericTableIface
30 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
31 if utils_folder
not in sys.path:
32 sys.path.insert(0, utils_folder)
33 from utils
import printNumericTables
35 DAAL_PREFIX = os.path.join(
'..',
'data')
38 trainDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'adaboost_train.csv')
40 testDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'adaboost_test.csv')
45 predictionResult =
None
46 testGroundTruth =
None
53 trainDataSource = FileDataSource(
54 trainDatasetFileName, DataSourceIface.notAllocateNumericTable,
55 DataSourceIface.doDictionaryFromContext
59 trainData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
60 trainGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
61 mergedData = MergedNumericTable(trainData, trainGroundTruth)
64 trainDataSource.loadDataBlock(mergedData)
67 algorithm = training.Batch()
70 algorithm.input.set(classifier.training.data, trainData)
71 algorithm.input.set(classifier.training.labels, trainGroundTruth)
74 trainingResult = algorithm.compute()
78 global predictionResult, testGroundTruth
81 testDataSource = FileDataSource(
82 testDatasetFileName, DataSourceIface.notAllocateNumericTable,
83 DataSourceIface.doDictionaryFromContext
87 testData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
88 testGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
89 mergedData = MergedNumericTable(testData, testGroundTruth)
92 testDataSource.loadDataBlock(mergedData)
95 algorithm = prediction.Batch()
98 algorithm.input.setTable(classifier.prediction.data, testData)
99 algorithm.input.setModel(classifier.prediction.model, trainingResult.get(classifier.training.model))
103 predictionResult = algorithm.compute()
107 testGroundTruth, predictionResult.get(classifier.prediction.prediction),
108 "Ground truth",
"Classification results",
109 "AdaBoost classification results (first 20 observations):", 20, flt64=
False
112 if __name__ ==
"__main__":