Python* API Reference for Intel® Data Analytics Acceleration Library 2019

logistic_dense_batch.py

1 # file: logistic_dense_batch.py
2 #===============================================================================
3 # Copyright 2014-2018 Intel Corporation.
4 #
5 # This software and the related documents are Intel copyrighted materials, and
6 # your use of them is governed by the express license under which they were
7 # provided to you (License). Unless the License provides otherwise, you may not
8 # use, modify, copy, publish, distribute, disclose or transmit this software or
9 # the related documents without Intel's prior written permission.
10 #
11 # This software and the related documents are provided as is, with no express
12 # or implied warranties, other than those that are expressly stated in the
13 # License.
14 #===============================================================================
15 
16 #
17 # ! Content:
18 # ! Python example of Logistic algorithm.
19 # !
20 # !*****************************************************************************
21 
22 #
23 ## <a name="DAAL-EXAMPLE-PY-LOGISTIC_BATCH"></a>
24 ## \example logistic_dense_batch.py
25 #
26 
27 import os
28 import sys
29 
30 import daal.algorithms.math.logistic as logistic
31 from daal.data_management import FileDataSource, DataSourceIface
32 
33 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
34 if utils_folder not in sys.path:
35  sys.path.insert(0, utils_folder)
36 from utils import printNumericTable
37 
38 # Input data set parameters
39 datasetName = os.path.join('..', 'data', 'batch', 'covcormoments_dense.csv')
40 
41 if __name__ == "__main__":
42 
43  # Retrieve the input data
44  dataSource = FileDataSource(datasetName,
45  DataSourceIface.doAllocateNumericTable,
46  DataSourceIface.doDictionaryFromContext)
47  dataSource.loadDataBlock()
48 
49  # Create an algorithm
50  algorithm = logistic.Batch()
51 
52  # Set an input object for the algorithm
53  algorithm.input.set(logistic.data, dataSource.getNumericTable())
54 
55  # Compute Logistic function
56  res = algorithm.compute()
57 
58  # Print the results of the algorithm
59  printNumericTable(res.get(logistic.value), "Logistic result (first 5 rows):", 5)

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