TuningSVMs
OpenML dataset with id 41978
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Full work available at URL: https://api.openml.org/data/v1/download/21381934/TuningSVMs.arff
Upload date: 17 July 2019
Copyright license: CC0
Dataset Characteristics
Number of classes: 2
Number of features: 81 (numeric: 80, symbolic: 1 and in total binary: 1 )
Number of instances: 156
Number of instances with missing values: 0
Number of missing values: 0
Author: Rafael G. Mantovani, Edesio Alcobaça, André L. D. Rossi, Joaquin Vanschoren, André C. P. L. F. de Carvalho Source: "A meta-learning recommender system for hyperparameter tuning: predicting when tuning improves SVM classifiers" - Information Sciences, volume 501, 2019. Please cite: 10.1016/j.ins.2019.06.005
This is a meta-dataset which describes the SVM hyperparameter tuning problem. The target attribute indicates whether tuning is required or default hyperparameter values are enough to each dataset (row). Targets were defined using a statistical labelling rule comparing the predictive performance of models induced with defaults values and tuned ones. In this version of the dataset, the labelling rule was set with 99% confidence.
This page was built for dataset: TuningSVMs
