% MLR SVM
% Experiment data obtained by running random configurations of an SVM through mlr on 106 different classification tasks from openml.
% For information on the algorithm and metrics, see: https://mlr.mlr-org.com/index.html
% 
% Features
% task_id: the task id on openml (navigate to openml/t/{task_id})
% dataset: the name of the dataset for which the task is defined
% learner: name of the mlr learner used in the experiment
% perf.mmce: mean misclassification error
% perf.logloss: log loss 
% traintime: time in seconds used for training
% predicttime: time in seconds used for making predictions
% kernel: value of the kernel hyperparameter
% cost: value of the cost hyperparameter
% gamma: value of the gamma hyperparameter for the radial kernel
% tolerance: value of the tolerance hyperparameter
% shrinking: value of the shrinking hyperparameter
% 'num.impute.selected.cpo': impute strategy for missing data
% fitted: logical indicating whether the fitted values should be computed and included in the model or not 
% degree: degree hyperparameter for the polynomial kernel
@relation 'mlr_svm_rng'
@attribute 'task_id' numeric
@attribute 'dataset' string
@attribute 'learner' string
@attribute 'perf.mmce' numeric
@attribute 'perf.logloss' numeric
@attribute 'traintime' numeric
@attribute 'predicttime' numeric
@attribute 'kernel' string
@attribute 'cost' numeric
@attribute 'gamma' numeric
@attribute 'tolerance' numeric
@attribute 'shrinking' string
@attribute 'num.impute.selected.cpo' string
@attribute 'fitted' string
@attribute 'degree' numeric
@data
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3893,"sylva_prior","classif.svm.radial",0.061549059918153,0.231209234023688,5530.775,56.269,"radial",0.016851,32.4721,0.000600589,"FALSE","impute.hist","FALSE",?
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