24 from daal.algorithms
import logistic_regression
25 from daal.algorithms.logistic_regression
import prediction, training
26 from daal.algorithms
import classifier
27 from daal.data_management
import (
28 FileDataSource, DataSourceIface, NumericTableIface, HomogenNumericTable,
29 MergedNumericTable, features
32 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
33 if utils_folder
not in sys.path:
34 sys.path.insert(0, utils_folder)
35 from utils
import printNumericTable, printNumericTables
37 DAAL_PREFIX = os.path.join(
'..',
'data')
40 trainDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'binary_cls_train.csv')
41 testDatasetFileName = os.path.join(DAAL_PREFIX,
'batch',
'binary_cls_test.csv')
48 predictionResult =
None
49 testGroundTruth =
None
55 trainDataSource = FileDataSource(
57 DataSourceIface.notAllocateNumericTable,
58 DataSourceIface.doDictionaryFromContext
62 trainData = HomogenNumericTable(nFeatures, 0, NumericTableIface.notAllocate)
63 trainGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.notAllocate)
64 mergedData = MergedNumericTable(trainData, trainGroundTruth)
67 trainDataSource.loadDataBlock(mergedData)
70 algorithm = training.Batch(nClasses)
73 algorithm.input.set(classifier.training.data, trainData)
74 algorithm.input.set(classifier.training.labels, trainGroundTruth)
77 trainingResult = algorithm.compute()
78 model = trainingResult.get(classifier.training.model)
79 printNumericTable(model.getBeta(),
"Logistic Regression coefficients:")
82 global testGroundTruth, predictionResult
85 testDataSource = FileDataSource(
87 DataSourceIface.notAllocateNumericTable,
88 DataSourceIface.doDictionaryFromContext
92 testData = HomogenNumericTable(nFeatures, 0, NumericTableIface.notAllocate)
93 testGroundTruth = HomogenNumericTable(1, 0, NumericTableIface.notAllocate)
94 mergedData = MergedNumericTable(testData, testGroundTruth)
97 testDataSource.loadDataBlock(mergedData)
100 algorithm = prediction.Batch(nClasses)
103 algorithm.input.setTable(classifier.prediction.data, testData)
104 algorithm.input.setModel(classifier.prediction.model, model)
108 predictionResult = algorithm.compute()
113 printNumericTable(predictionResult.get(classifier.prediction.prediction),
"Logistic regression prediction results (first 10 rows):",10)
114 printNumericTable(testGroundTruth,
"Ground truth (first 10 rows):",10)
116 if __name__ ==
"__main__":