22 from daal.algorithms.svm
import training, prediction
23 from daal.algorithms
import kernel_function, classifier
24 from daal.data_management
import DataSourceIface, FileDataSource
26 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
27 if utils_folder
not in sys.path:
28 sys.path.insert(0, utils_folder)
29 from utils
import printNumericTables, createSparseTable
32 DATA_PREFIX = os.path.join(
'..',
'data',
'batch')
34 trainDatasetFileName = os.path.join(DATA_PREFIX,
'svm_two_class_train_csr.csv')
35 trainLabelsFileName = os.path.join(DATA_PREFIX,
'svm_two_class_train_labels.csv')
36 testDatasetFileName = os.path.join(DATA_PREFIX,
'svm_two_class_test_csr.csv')
37 testLabelsFileName = os.path.join(DATA_PREFIX,
'svm_two_class_test_labels.csv')
40 kernel = kernel_function.linear.Batch(method=kernel_function.linear.fastCSR)
44 predictionResult =
None
51 trainLabelsDataSource = FileDataSource(
52 trainLabelsFileName, DataSourceIface.doAllocateNumericTable,
53 DataSourceIface.doDictionaryFromContext
57 trainData = createSparseTable(trainDatasetFileName)
60 trainLabelsDataSource.loadDataBlock()
63 algorithm = training.Batch()
65 algorithm.parameter.kernel = kernel
66 algorithm.parameter.cacheSize = 40000000
69 algorithm.input.set(classifier.training.data, trainData)
70 algorithm.input.set(classifier.training.labels, trainLabelsDataSource.getNumericTable())
73 trainingResult = algorithm.compute()
77 global predictionResult
80 testData = createSparseTable(testDatasetFileName)
83 algorithm = prediction.Batch()
85 algorithm.parameter.kernel = kernel
88 algorithm.input.setTable(classifier.prediction.data, testData)
90 algorithm.input.setModel(classifier.prediction.model, trainingResult.get(classifier.training.model))
96 predictionResult = algorithm.getResult()
102 testLabelsDataSource = FileDataSource(
103 testLabelsFileName, DataSourceIface.doAllocateNumericTable,
104 DataSourceIface.doDictionaryFromContext
107 testLabelsDataSource.loadDataBlock()
108 testGroundTruth = testLabelsDataSource.getNumericTable()
111 testGroundTruth, predictionResult.get(classifier.prediction.prediction),
112 "Ground truth\t",
"Classification results",
113 "SVM classification results (first 20 observations):", 20, flt64=
False
116 if __name__ ==
"__main__":