| Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model ARS Parmezan, VMA Souza, GE Batista Information Sciences 484, 302-337, 2019 | 353 | 2019 |
| Metalearning for choosing feature selection algorithms in data mining: Proposal of a new framework ARS Parmezan, HD Lee, FC Wu Expert Systems with Applications 75, 1-24, 2017 | 63 | 2017 |
| Automatic recommendation of feature selection algorithms based on dataset characteristics ARS Parmezan, HD Lee, N Spolaôr, FC Wu Expert Systems with Applications 185, 115589, 2021 | 36 | 2021 |
| Dermoscopic assisted diagnosis in melanoma: Reviewing results, optimizing methodologies and quantifying empirical guidelines HD Lee, AI Mendes, N Spolaor, JT Oliva, ARS Parmezan, FC Wu, ... Knowledge-Based Systems 158, 9-24, 2018 | 33 | 2018 |
| A study of the use of complexity measures in the similarity search process adopted by kNN algorithm for time series prediction ARS Parmezan, GEAPA Batista Machine Learning and Applications (ICMLA), 2015 IEEE 14th International …, 2015 | 31 | 2015 |
| Changes in the wing-beat frequency of bees and wasps depending on environmental conditions: a study with optical sensors ARS Parmezan, V Souza, I Žliobaitė, GE Batista Apidologie 52 (4), 731-748, 2021 | 24 | 2021 |
| Fine-tuning pre-trained neural networks for medical image classification in small clinical datasets N Spolaôr, HD Lee, AI Mendes, CV Nogueira, ARS Parmezan, ... Multimedia Tools and Applications 83 (9), 27305-27329, 2024 | 18 | 2024 |
| Towards Hierarchical Classification of Data Streams ARS Parmezan, VMA Souza, GE Batista Iberoamerican Congress on Pattern Recognition, 314-322, 2018 | 18 | 2018 |
| Efficient unsupervised drift detector for fast and high-dimensional data streams VMA Souza, ARS Parmezan, FA Chowdhury, A Mueen Knowledge and Information Systems 63 (6), 1497-1527, 2021 | 16 | 2021 |
| ICMC-USP Time Series Prediction Repository ARS Parmezan, GEAPA Batista Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo …, 2014 | 15 | 2014 |
| A Combination of Local Approaches for Hierarchical Music Genre Classification ARS Parmezan, DF Silva, GE Batista International Society for Music Information Retrieval Conference, 740-747, 2020 | 12 | 2020 |
| Hierarchical classification of pollinating flying insects under changing environments ARS Parmezan, VMA Souza, A Seth, I Žliobaitė, GE Batista Ecological Informatics 70, 101751, 2022 | 9 | 2022 |
| Predição de séries temporais por similaridade ARS Parmezan Dissertação (Mestrado em Ciências de Computação e Matemática Computacional …, 2016 | 9 | 2016 |
| Time Series Prediction via Similarity Search: Exploring Invariances, Distance Measures and Ensemble Functions ARS Parmezan, VMA Souza, GE Batista IEEE Access 10, 78022-78043, 2022 | 8 | 2022 |
| Descrição de Modelos Estatísticos e de Aprendizado de Máquina para Predição de Séries Temporais ARS Parmezan, GEAPA Batista Relatório Técnico, Universidade de São Paulo, São Carlos, 1-96, 2016 | 7 | 2016 |
| A Graph-Based Spatial Cross-Validation Approach for Assessing Models Learned with Selected Features to Understand Election Results TP Da Silva, ARS Parmezan, GE Batista 2021 20th IEEE International Conference on Machine Learning and Applications …, 2021 | 6 | 2021 |
| A video indexing and retrieval computational prototype based on transcribed speech N Spolaôr, HD Lee, WSR Takaki, LA Ensina, ARS Parmezan, JT Oliva, ... Multimedia Tools and Applications 80 (25), 33971-34017, 2021 | 6 | 2021 |
| Analyzing spatio-temporal voting patterns in Brazilian elections through a simple data science pipeline LHM Jacintho, TP da Silva, ARS Parmezan, G Batista Journal of Information and Data Management 12 (1), 31-47, 2021 | 5 | 2021 |
| Estudo Comparativo entre Métodos de Seleção de Atributos Baseados em Medidas de Precisão e Correlação Aplicados à Bases de Dados ARS Parmezan, HD Lee, FC Wu XVIII Simpósio Internacional de Iniciação Científica da Universidade de São …, 2010 | 5 | 2010 |
| Avaliação de Métodos para Seleção de Atributos Importantes para Aprendizado de Máquina Supervisionado no Processo de Mineração de Dados ARS Parmezan, HD Lee, N Spolaôr, FC Wu Relatório Técnico, Universidade Estadual do Oeste do Paraná, Foz do Iguaçu, 1-58, 2012 | 4 | 2012 |
Gustavo Enrique BatistaAssociate Professor, School of Computer Science and Engineering, University of New South WalesΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα cse.unsw.edu.au
