22 from daal.algorithms.svm
import training, prediction
23 from daal.algorithms
import kernel_function, classifier
24 from daal.data_management
import (
25 DataSourceIface, FileDataSource, 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
34 DATA_PREFIX = os.path.join(
'..',
'data',
'batch')
36 trainDatasetFileName = os.path.join(DATA_PREFIX,
'svm_two_class_train_dense.csv')
37 testDatasetFileName = os.path.join(DATA_PREFIX,
'svm_two_class_test_dense.csv')
42 kernel = kernel_function.linear.Batch()
46 predictionResult =
None
47 testGroundTruth =
None
54 trainDataSource = FileDataSource(
55 trainDatasetFileName, DataSourceIface.notAllocateNumericTable,
56 DataSourceIface.doDictionaryFromContext
60 trainData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
61 trainGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
62 mergedData = MergedNumericTable(trainData, trainGroundTruth)
65 trainDataSource.loadDataBlock(mergedData)
68 algorithm = training.Batch()
70 algorithm.parameter.kernel = kernel
71 algorithm.parameter.cacheSize = 600000000
74 algorithm.input.set(classifier.training.data, trainData)
75 algorithm.input.set(classifier.training.labels, trainGroundTruth)
78 trainingResult = algorithm.compute()
82 global predictionResult, testGroundTruth
85 testDataSource = FileDataSource(
86 testDatasetFileName, DataSourceIface.notAllocateNumericTable,
87 DataSourceIface.doDictionaryFromContext
91 testData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
92 testGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
93 mergedData = MergedNumericTable(testData, testGroundTruth)
96 testDataSource.loadDataBlock(mergedData)
99 algorithm = prediction.Batch()
101 algorithm.parameter.kernel = kernel
104 algorithm.input.setTable(classifier.prediction.data, testData)
105 algorithm.input.setModel(classifier.prediction.model, trainingResult.get(classifier.training.model))
111 predictionResult = algorithm.getResult()
117 testGroundTruth, predictionResult.get(classifier.prediction.prediction),
118 "Ground truth\t",
"Classification results",
119 "SVM classification results (first 20 observations):", 20, flt64=
False
122 if __name__ ==
"__main__":