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 "file=@weather.numeric.arff" -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/5b28b61d1a2bd3000121a183returns:
{ "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/5b28b61e1a2bd3000121a189will 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