47 from daal.algorithms.kdtree_knn_classification
import training, prediction
48 from daal.algorithms
import classifier
49 from daal.data_management
import (
50 DataSourceIface, FileDataSource, HomogenNumericTable, MergedNumericTable, NumericTableIface
53 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
54 if utils_folder
not in sys.path:
55 sys.path.insert(0, utils_folder)
56 from utils
import printNumericTables
58 DAAL_PREFIX = os.path.join(
'..',
'data')
61 trainDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'k_nearest_neighbors_train.csv')
62 testDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'k_nearest_neighbors_test.csv')
67 predictionResult =
None
74 trainDataSource = FileDataSource(
75 trainDatasetFileName, DataSourceIface.notAllocateNumericTable,
76 DataSourceIface.doDictionaryFromContext
80 trainData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
81 trainGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
82 mergedData = MergedNumericTable(trainData, trainGroundTruth)
85 trainDataSource.loadDataBlock(mergedData)
88 algorithm = training.Batch()
91 algorithm.input.set(classifier.training.data, trainData)
92 algorithm.input.set(classifier.training.labels, trainGroundTruth)
95 trainingResult = algorithm.compute()
99 global trainingResult, predictionResult
102 testDataSource = FileDataSource(
103 testDatasetFileName, DataSourceIface.doAllocateNumericTable,
104 DataSourceIface.doDictionaryFromContext
108 testData = HomogenNumericTable(nFeatures, 0, NumericTableIface.doNotAllocate)
109 testGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.doNotAllocate)
110 mergedData = MergedNumericTable(testData, testGroundTruth)
113 testDataSource.loadDataBlock(mergedData)
116 algorithm = prediction.Batch()
119 algorithm.input.setTable(classifier.prediction.data, testData)
120 algorithm.input.setModel(classifier.prediction.model, trainingResult.get(classifier.training.model))
123 predictionResult = algorithm.compute()
125 testGroundTruth, predictionResult.get(classifier.prediction.prediction),
126 "Ground truth",
"Classification results",
127 "KD-tree based kNN classification results (first 20 observations):", 20, flt64=
False
130 if __name__ ==
"__main__":