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Rafael Gomes Mantovani
Rafael Gomes Mantovani
Federal Technology University - Paraná, campus of Apucarana
Verified email at utfpr.edu.br
Title
Cited by
Cited by
Year
Openml benchmarking suites
B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ...
arXiv preprint arXiv:1708.03731, 2017
722017
Effectiveness of random search in SVM hyper-parameter tuning
RG Mantovani, ALD Rossi, J Vanschoren, B Bischl, AC De Carvalho
2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015
722015
Hyper-parameter tuning of a decision tree induction algorithm
RG Mantovani, T Horváth, R Cerri, J Vanschoren, AC de Carvalho
2016 5th Brazilian Conference on Intelligent Systems (BRACIS), 37-42, 2016
712016
To tune or not to tune: recommending when to adjust SVM hyper-parameters via meta-learning
RG Mantovani, ALD Rossi, J Vanschoren, B Bischl, AC Carvalho
2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015
432015
Applying multi-label techniques in emotion identification of short texts
AMG Almeida, R Cerri, EC Paraiso, RG Mantovani, SB Junior
Neurocomputing 320, 35-46, 2018
382018
Machine learning hyperparameter selection for contrast limited adaptive histogram equalization
GFC Campos, SM Mastelini, GJ Aguiar, RG Mantovani, LF Melo, ...
EURASIP Journal on Image and Video Processing 2019 (1), 1-18, 2019
352019
A meta-learning recommender system for hyperparameter tuning: Predicting when tuning improves SVM classifiers
RG Mantovani, ALD Rossi, E Alcobaca, J Vanschoren, AC de Carvalho
Information Sciences 501, 193-221, 2019
332019
Storage time prediction of pork by Computational Intelligence
APAC Barbon, S Barbon Jr, RG Mantovani, EM Fuzyi, LM Peres, AM Bridi
Computers and Electronics in Agriculture 127, 368-375, 2016
322016
Pattern recognition of lower member skin ulcers in medical images with machine learning algorithms
JL Seixas, S Barbon, RG Mantovani
2015 IEEE 28th International Symposium on Computer-Based Medical Systems, 50-53, 2015
232015
Machine learning applied to near-infrared spectra for chicken meat classification
S Barbon, APA Costa Barbon, RG Mantovani, DF Barbin
Journal of Spectroscopy 2018, 2018
202018
A meta-learning approach for selecting image segmentation algorithm
GJ Aguiar, RG Mantovani, SM Mastelini, AC de Carvalho, GFC Campos, ...
Pattern Recognition Letters 128, 480-487, 2019
192019
A meta-learning approach for recommendation of image segmentation algorithms
GFC Campos, S Barbon, RG Mantovani
2016 29th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI …, 2016
172016
An empirical study on hyperparameter tuning of decision trees
RG Mantovani, T Horváth, R Cerri, SB Junior, J Vanschoren, ...
arXiv preprint arXiv:1812.02207, 2018
162018
Meta-learning Recommendation of Default Hyper-parameter Values for SVMs in Classification Tasks.
RG Mantovani, ALD Rossi, J Vanschoren, AC de Carvalho
MetaSel@ PKDD/ECML, 80-92, 2015
132015
Effects of random sampling on svm hyper-parameter tuning
T Horváth, RG Mantovani, AC de Carvalho
International Conference on Intelligent Systems Design and Applications, 268-278, 2016
122016
Multi-label feature selection techniques for hierarchical multi-label protein function prediction
R Cerri, RG Mantovani, MP Basgalupp, AC de Carvalho
2018 International Joint Conference on Neural Networks (IJCNN), 1-7, 2018
72018
Edesio Alcobaça, Joaquin Vanschoren, and André CPLF de Carvalho. 2019. A meta-learning recommender system for hyperparameter tuning: Predicting when tuning improves SVM classifiers
RG Mantovani, ALD Rossi
Information Sciences 501, 193-221, 0
6
Openml benchmarking suites. 2019
B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ...
URL https://arxiv. org/abs/1708.03731, 0
6
Decision Trees for the detection of skin lesion patterns in lower limbs ulcers
JL Seixas, RG Mantovani
2016 International Conference on Computational Science and Computational …, 2016
52016
Towards meta-learning for multi-target regression problems
GJ Aguiar, EJ Santana, SM Mastelini, RG Mantovani, SB Júnior
2019 8th Brazilian Conference on Intelligent Systems (BRACIS), 377-382, 2019
42019
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