47 from daal.algorithms.decision_tree.regression
import prediction, training
48 from daal.data_management
import (
49 FileDataSource, DataSourceIface, NumericTableIface, HomogenNumericTable, MergedNumericTable
52 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
53 if utils_folder
not in sys.path:
54 sys.path.insert(0, utils_folder)
55 from utils
import printNumericTables
57 DAAL_PREFIX = os.path.join(
'..',
'data')
60 trainDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'decision_tree_train.csv')
61 pruneDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'decision_tree_prune.csv')
62 testDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'decision_tree_test.csv')
68 predictionResult =
None
69 testGroundTruth =
None
76 trainDataSource = FileDataSource(
78 DataSourceIface.notAllocateNumericTable,
79 DataSourceIface.doDictionaryFromContext
83 trainData = HomogenNumericTable(nFeatures, 0, NumericTableIface.notAllocate)
84 trainGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.notAllocate)
85 mergedData = MergedNumericTable(trainData, trainGroundTruth)
88 trainDataSource.loadDataBlock(mergedData)
91 pruneDataSource = FileDataSource(
93 DataSourceIface.notAllocateNumericTable,
94 DataSourceIface.doDictionaryFromContext
98 pruneData = HomogenNumericTable(nFeatures, 0, NumericTableIface.notAllocate)
99 pruneGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.notAllocate)
100 pruneMergedData = MergedNumericTable(pruneData, pruneGroundTruth)
103 pruneDataSource.loadDataBlock(pruneMergedData)
106 algorithm = training.Batch()
109 algorithm.input.set(training.data, trainData)
110 algorithm.input.set(training.dependentVariables, trainGroundTruth)
111 algorithm.input.set(training.dataForPruning, pruneData)
112 algorithm.input.set(training.dependentVariablesForPruning, pruneGroundTruth)
115 trainingResult = algorithm.compute()
116 model = trainingResult.get(training.model)
119 global testGroundTruth, predictionResult
122 testDataSource = FileDataSource(
124 DataSourceIface.notAllocateNumericTable,
125 DataSourceIface.doDictionaryFromContext
129 testData = HomogenNumericTable(nFeatures, 0, NumericTableIface.notAllocate)
130 testGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.notAllocate)
131 mergedData = MergedNumericTable(testData, testGroundTruth)
134 testDataSource.loadDataBlock(mergedData)
137 algorithm = prediction.Batch()
140 print(
"Number of columns: {}".format(testData.getNumberOfColumns()))
141 algorithm.input.setTable(prediction.data, testData)
142 algorithm.input.setModel(prediction.model, model)
145 predictionResult = algorithm.compute()
150 printNumericTables(testGroundTruth, predictionResult.get(prediction.prediction),
151 "Ground truth",
"Regression results",
152 "Decision tree regression results (first 20 observations):",
155 if __name__ ==
"__main__":