![]() ![]() multi_resultset_full ( 0, comparison_col )) print ( tester. header ( comparison_col )) print ( tester. ![]() resultmatrix = matrix comparison_col = data. load_file ( result ) from weka.experiments import Tester, ResultMatrix matrix = ResultMatrix ( classname = "" ) tester = Tester ( classname = "" ) tester. You can generate HTML documentation using the make html command in the doc directory. More Data Mining with Weka: online course from the University of WaikatoClass 4 - Lesson 1: Attribute selection using the 'wrapper' method. Also, check out the sphinx documentation in the doc directory. loader_for_file ( result ) data = loader. See python-weka-wrapper-examples repository for example code on the various APIs. Datasets = classifiers = result = "exp.arff" from weka.experiments import SimpleCrossValidationExperiment exp = SimpleCrossValidationExperiment ( classification = True, runs = 10, folds = 10, datasets = datasets, classifiers = classifiers, result = result ) exp.
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