Stebėti
Gustavo Enrique Batista
Gustavo Enrique Batista
Kiti vardaiGustavo Batista, Gustavo Enrique de Almeida Prado Alves Batista, Gustavo E.A.P.A. Batista
Associate Professor, School of Computer Science and Engineering, University of New South Wales
Patvirtintas el. paštas cse.unsw.edu.au - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
A study of the behavior of several methods for balancing machine learning training data
GE Batista, RC Prati, MC Monard
ACM SIGKDD Explorations Newsletter 6 (1), 20-29, 2004
49432004
Searching and mining trillions of time series subsequences under dynamic time warping
T Rakthanmanon, B Campana, A Mueen, G Batista, B Westover, Q Zhu, ...
Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012
13962012
An analysis of four missing data treatment methods for supervised learning
GE Batista, MC Monard
Applied Artificial Intelligence 17 (5-6), 519-533, 2003
11832003
The ucr time series classification archive
Y Chen, E Keogh, B Hu, N Begum, A Bagnall, A Queen, G Batista
http://www.cs.ucr.edu/~eamonn/time_series_data/, 2015
10952015
A Study of K-Nearest Neighbour as an Imputation Method
GE Batista, MC Monard
HIS 87 (251-260), 48, 2002
6112002
Balancing training data for automated annotation of keywords: a case study
G Batista, AL Bazan, MC Monard
Proceedings of the Second Brazilian Workshop on Bioinformatics, 35-43, 2003
5632003
Class imbalances versus class overlapping: an analysis of a learning system behavior
R Prati, G Batista, M Monard
MICAI 2004: Advances in Artificial Intelligence, 312-321, 2004
4992004
A Complexity-Invariant Distance Measure for Time Series
G Batista, X Wang, E Keogh
SDM-2011: Proceedings of SIAM International Conference on Data Mining, 2011
4692011
CID: an efficient complexity-invariant distance for time series
GE Batista, EJ Keogh, OM Tataw, VMA De Souza
Data Mining and Knowledge Discovery 28 (3), 634-669, 2014
4652014
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
3582019
Addressing big data time series: Mining trillions of time series subsequences under dynamic time warping
T Rakthanmanon, B Campana, A Mueen, G Batista, B Westover, Q Zhu, ...
ACM Transactions on Knowledge Discovery from Data (TKDD) 7 (3), 1-31, 2013
3402013
Hexagon-ML: the UCR time series classification archive, October 2018
HA Dau, E Keogh, K Kamgar, CCM Yeh, Y Zhu, S Gharghabi, ...
336*2018
The UCR time series classification archive
HA Dau, E Keogh, K Kamgar, CCM Yeh, Y Zhu, S Gharghabi, ...
URL https://www. cs. ucr. edu/~ eamonn/time_series_data_2018, 2018
3182018
Class imbalance revisited: a new experimental setup to assess the performance of treatment methods
RC Prati, GE Batista, DF Silva
Knowledge and Information Systems 45, 247-270, 2015
2232015
Fast unsupervised online drift detection using incremental kolmogorov-smirnov test
DM dos Reis, P Flach, S Matwin, G Batista
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016
2062016
Flying insect classification with inexpensive sensors
Y Chen, A Why, G Batista, A Mafra-Neto, E Keogh
Journal of insect behavior 27 (5), 657-677, 2014
1812014
DTW-D: time series semi-supervised learning from a single example
Y Chen, B Hu, E Keogh, GE Batista
Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013
1722013
Speeding up all-pairwise dynamic time warping matrix calculation
DF Silva, GE Batista
Proceedings of the 2016 SIAM International Conference on Data Mining, 837-845, 2016
1712016
Challenges in Benchmarking Stream Learning Algorithms with Real-world Data
V Souza, DM Reis, AG Maletzke, GE Batista
Data Mining and Knowledge Discovery 34, 1805–1858, 2020
1632020
Curvas ROC para avaliação de classificadores
RC Prati, G Batista, MC Monard
Revista IEEE América Latina 6 (2), 215-222, 2008
162*2008
Sistema negali atlikti operacijos. Bandykite vėliau dar kartą.
Straipsniai 1–20