Newton Spolaôr
Newton Spolaôr
Western Paraná State University
Zweryfikowany adres z unioeste.br - Strona główna
Cytowane przez
Cytowane przez
A Comparison of Multi-label Feature Selection Methods using the Problem Transformation Approach
N Spolaôr, EA Cherman, MC Monard, HD Lee
Electronic Notes in Theoretical Computer Science 292, 135-151, 2013
ReliefF for Multi-label Feature Selection
N Spolaor, EA Cherman, MC Monard, HD Lee
Intelligent Systems (BRACIS), 2013 Brazilian Conference on, 6-11, 2013
Robotics applications grounded in learning theories on tertiary education: A systematic review
N Spolaôr, FBV Benitti
Computers & Education 112, 97-107, 2017
A systematic review of multi-label feature selection and a new method based on label construction
N Spolaôr, MC Monard, G Tsoumakas, HD Lee
Neurocomputing 180, 3-15, 2016
How Have Robots Supported STEM Teaching?
FBV Benitti, N Spolaôr
Robotics in STEM Education, 103-129, 2017
Analysis of complexity indices for classification problems: cancer gene expression data
AC Lorena, IG Costa, N Spolaôr, MCP de Souto
Neurocomputing 75 (1), 33-42, 2012
A Framework to Generate Synthetic Multi-label Datasets
JT Tomás, N Spolaôr, EA Cherman, MC Monard
Electronic Notes in Theoretical Computer Science 302, 155-176, 2014
Filter approach feature selection methods to support multi-label learning based on relieff and information gain
N Spolaôr, EA Cherman, MC Monard, HD Lee
Brazilian Symposium on Artificial Intelligence, 72-81, 2012
Feature selection before EEG classification supports the diagnosis of Alzheimer’s disease
LR Trambaiolli, N Spolaôr, AC Lorena, R Anghinah, JR Sato
Clinical Neurophysiology 128 (10), 2058-2067, 2017
Evaluating Feature Selection Methods for Multi-Label Text Classification
N Spolaôr, G Tsoumakas
Multi-objective genetic algorithm evaluation in feature selection
N Spolaôr, AC Lorena, HD Lee
International Conference on Evolutionary Multi-Criterion Optimization, 462-476, 2011
Prototype system for feature extraction, classification and study of medical images
JT Oliva, HD Lee, N Spolaôr, CSR Coy, FC Wu
Expert Systems with Applications 63, 267-283, 2016
Using ReliefF for multi-label feature selection
N Spolaôr, EA Cherman, MC Monard
Conferencia Latinoamericana de Informática, 960-975, 2011
Dermoscopic assisted diagnosis in melanoma: Reviewing results, optimizing methodologies and quantifying empirical guidelines
HD Lee, AI Mendes, N Spolaôr, JT Oliva, ARS Parmezan, FC Wu, ...
Knowledge-Based Systems 158, 9-24, 2018
Lazy multi-label learning algorithms based on mutuality strategies
EA Cherman, N Spolaôr, J Valverde-Rebaza, MC Monard
Journal of Intelligent & Robotic Systems 80 (1), 261-276, 2015
A systematic review to identify feature selection publications in multi-labeled data
N Spolaôr, MC Monard, HD Lee
A systematic review on content-based video retrieval
N Spolaôr, HD Lee, WSR Takaki, LA Ensina, CSR Coy, FC Wu
Engineering Applications of Artificial Intelligence 90, 103557, 2020
Label Construction for Multi-label Feature Selection
N Spolaor, M Monard, G Tsoumakas, H Lee
Complexity measures of supervised classifications tasks: a case study for cancer gene expression data
MCP de Souto, AC Lorena, N Spolaôr, IG Costa
Neural Networks (IJCNN), The 2010 International Joint Conference on, 1-7, 2010
Use of multiobjective genetic algorithms in feature selection
N Spolaôr, AC Lorena, HD Lee
2010 Eleventh Brazilian Symposium on Neural Networks, 146-151, 2010
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