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Commandline Examples with Curl

Create a model

POST a local arff file to an algorithm (example)

  • POST the data to the NaiveBayes algorithm

    curl -X POST "https://jguweka.prod.openrisknet.org/algorithm/NaiveBayes" -H  "accept: text/uri-list"  -H  "Content-Type: multipart/form-data" -F "[email protected]" -F "batchSize=100" -F "useKernelEstimator=0" -F "useSupervisedDiscretization=0" -F "validation=CrossValidation" -F "validationNum=10"

    will return a task:

    https://jguweka.prod.openrisknet.org/task/5b28b61d1a2bd3000121a183

  • check the task status:

    curl -X GET https://jguweka.prod.openrisknet.org/task/5b28b61d1a2bd3000121a183

    returns:

    {
  "date" : "2018-06-19T07:51:56.000Z",
  "errorReport" : null,
  "uri" : "https://jguweka.prod.openrisknet.org/task/5b28b61d1a2bd3000121a183",
  "status" : "COMPLETED",
  "taskID" : "5b28b61d1a2bd3000121a183",
  "URI" : "https://jguweka.prod.openrisknet.org/task/5b28b61d1a2bd3000121a183",
  "resultURI" : "https://jguweka.prod.openrisknet.org/model/5b28b61e1a2bd3000121a189",
  "creator" : "NaiveBayes",
  "step" : "SAVED",
  "title" : "NaiveBayes algorithm",
  "hasStatus" : "COMPLETED",
  "description" : "Training data on NaiveBayes algorithm.",
  "percentageCompleted" : 100.0
}

    status is COMPLETED and the resultURI of the model is https://jguweka.prod.openrisknet.org/model/5b28b61e1a2bd3000121a189

  • retrieve the model as plain text representation

    curl -H "accept: text/plain"  https://jguweka.prod.openrisknet.org/model/5b28b61e1a2bd3000121a189

    will return:

    Naive Bayes Classifier

                 Class
Attribute          yes      no
                (0.63)  (0.38)
===============================
outlook
  sunny             3.0     4.0
  overcast          5.0     1.0
  rainy             4.0     3.0
  [total]          12.0     8.0

temperature
  mean          72.9697 74.8364
  std. dev.      5.2304   7.384
  weight sum          9       5
  precision      1.9091  1.9091

humidity
  mean          78.8395 86.1111
  std. dev.      9.8023  9.2424
  weight sum          9       5
  precision      3.4444  3.4444

windy
  TRUE              4.0     4.0
  FALSE             7.0     3.0
  [total]          11.0     7.0



=== Crossvalidation Results ===

Correctly Classified Instances           9               64.2857 %
Incorrectly Classified Instances         5               35.7143 %
Kappa statistic                          0.1026
Mean absolute error                      0.4649
Root mean squared error                  0.543 
Relative absolute error                 97.6254 %
Root relative squared error            110.051  %
Total Number of Instances               14     

=== Detailed Accuracy By Class ===

                 TP Rate  FP Rate  Precision  Recall   F-Measure  MCC      ROC Area  PRC Area  Class
                 0.889    0.800    0.667      0.889    0.762      0.122    0.444     0.633     yes
                 0.200    0.111    0.500      0.200    0.286      0.122    0.444     0.397     no
Weighted Avg.    0.643    0.554    0.607      0.643    0.592      0.122    0.444     0.548     


=== Confusion Matrix ===

 a b   <-- classified as
 8 1 | a = yes
 4 1 | b = no


Model build options:
weka.classifiers.bayes.NaiveBayes