48 from daal.algorithms.kdtree_knn_classification
import training, prediction
49 from daal.algorithms
import classifier
50 from daal.data_management
import (
51 DataSourceIface, FileDataSource, HomogenNumericTable, MergedNumericTable, NumericTableIface
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 trainDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'k_nearest_neighbors_train.csv')
63 testDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'k_nearest_neighbors_test.csv')
68 predictionResult =
None
75 trainDataSource = FileDataSource(
76 trainDatasetFileName, DataSourceIface.notAllocateNumericTable,
77 DataSourceIface.doDictionaryFromContext
81 trainData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
82 trainGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
83 mergedData = MergedNumericTable(trainData, trainGroundTruth)
86 trainDataSource.loadDataBlock(mergedData)
89 algorithm = training.Batch()
92 algorithm.input.set(classifier.training.data, trainData)
93 algorithm.input.set(classifier.training.labels, trainGroundTruth)
96 trainingResult = algorithm.compute()
100 global trainingResult, predictionResult
103 testDataSource = FileDataSource(
104 testDatasetFileName, DataSourceIface.doAllocateNumericTable,
105 DataSourceIface.doDictionaryFromContext
109 testData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
110 testGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
111 mergedData = MergedNumericTable(testData, testGroundTruth)
114 testDataSource.loadDataBlock(mergedData)
117 algorithm = prediction.Batch()
120 algorithm.input.setTable(classifier.prediction.data, testData)
121 algorithm.input.setModel(classifier.prediction.model, trainingResult.get(classifier.training.model))
124 predictionResult = algorithm.compute()
126 testGroundTruth, predictionResult.get(classifier.prediction.prediction),
127 "Ground truth",
"Classification results",
128 "KD-tree based kNN classification results (first 20 observations):", 20, flt64=
False
131 if __name__ ==
"__main__":