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ORCIDAna Carolina Lorena
Person information
- affiliation: Federal University of ABC, Center of Mathematics, Computation and Cognition, Brazil
- affiliation: Federal University of São Paulo, Institute of Science and Technology, São José dos Campos, Brazil
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2020 – today
- 2024
[j43]Ana Carolina Lorena
, Pedro Yuri Arbs Paiva, Ricardo B. C. Prudêncio:
Trusting My Predictions: On the Value of Instance-Level Analysis. ACM Comput. Surv. 56(7): 167:1-167:28 (2024)- [j42]João Luiz Junho Pereira, Kate Smith-Miles, Mario Andrés Muñoz, Ana Carolina Lorena:
Optimal selection of benchmarking datasets for unbiased machine learning algorithm evaluation. Data Min. Knowl. Discov. 38(2): 461-500 (2024) - [j41]João Luiz Junho Pereira, Matheus Brendon Francisco, Benedict Jun Ma, Guilherme Ferreira Gomes, Ana Carolina Lorena:
Golden lichtenberg algorithm: a fibonacci sequence approach applied to feature selection. Neural Comput. Appl. 36(32): 20493-20511 (2024) - [c62]Maria Gabriela Valeriano, João Luiz Junho Pereira, Carlos Roberto Veiga Kiffer, Ana Carolina Lorena:
Explaining instances in the health domain based on the exploration of a dataset's hardness embedding. GECCO Companion 2024: 1598-1606 - [c61]Eduardo Vargas Ferreira, Ricardo Bastos Cavalcante Prudêncio, Ana Carolina Lorena:
Measuring Latent Traits of Instance Hardness and Classifier Ability using Boltzmann Machines. IJCNN 2024: 1-8 - [c60]Ricardo B. C. Prudêncio, Ana Carolina Lorena, Telmo de Menezes e Silva Filho, Patrícia Drapal, Maria Gabriela Valeriano:
Assessor Models for Explaining Instance Hardness in Classification Problems. IJCNN 2024: 1-8 - 2023
- [c59]Eduardo Vargas Ferreira, Ana Carolina Lorena:
Machine Teaching: An Explainable Machine Learning Model for Individualized Education. BRACIS (1) 2023: 321-336 - [c58]Maria Gabriela Valeriano, Pedro Yuri Arbs Paiva, Carlos Roberto Veiga Kiffer, Ana Carolina Lorena:
A Framework for Characterizing What Makes an Instance Hard to Classify. BRACIS (2) 2023: 353-367 - [c57]Fernanda A. Melo, André C. P. L. F. de Carvalho, Ana Carolina Lorena, Luís Paulo F. Garcia:
Model Performance Prediction: A Meta-Learning Approach for Concept Drift Detection. HAIS 2023: 51-62 - [c56]Carmen Lancho, Marcilio C. P. de Souto, Ana Carolina Lorena, Isaac Martín de Diego:
Complexity-Driven Sampling for Bagging. IDEAL 2023: 15-21 - [e2]Albert Bifet, Ana Carolina Lorena, Rita P. Ribeiro, João Gama, Pedro H. Abreu:
Discovery Science - 26th International Conference, DS 2023, Porto, Portugal, October 9-11, 2023, Proceedings. Lecture Notes in Computer Science 14276, Springer 2023, ISBN 978-3-031-45274-1 [contents] - 2022
- [j40]Rodrigo Francisquini, Ana Carolina Lorena, Mariá C. V. Nascimento:
Community-based anomaly detection using spectral graph filtering. Appl. Soft Comput. 118: 108489 (2022) - [j39]Pedro Yuri Arbs Paiva, Camila Castro Moreno, Kate Smith-Miles, Maria Gabriela Valeriano, Ana Carolina Lorena:
Relating instance hardness to classification performance in a dataset: a visual approach. Mach. Learn. 111(8): 3085-3123 (2022) - [c55]Luiz Henrique dos Santos Fernandes, Kate Smith-Miles, Ana Carolina Lorena:
Generating Diverse Clustering Datasets with Targeted Characteristics. BRACIS (1) 2022: 398-412 - [c54]Maria Gabriela Valeriano, Carlos Roberto Veiga Kiffer, Giane Higino, Paloma Zanão, Dulce A. Barbosa, Patrícia A. Moreira, Paulo Caleb J. L. Santos, Renato Grinbaum, Ana Carolina Lorena:
Let the data speak: analysing data from multiple health centers of the São Paulo metropolitan area for COVID-19 clinical deterioration prediction. CCGRID 2022: 948-951 - [i4]Rodrigo Francisquini, Ana Carolina Lorena, Mariá C. V. Nascimento:
Community-based anomaly detection using spectral graph filtering. CoRR abs/2201.09936 (2022) - [i3]Gustavo P. Torquette, Victor S. Nunes, Pedro Yuri Arbs Paiva, Lourenço B. C. Neto, Ana Carolina Lorena:
Characterizing instance hardness in classification and regression problems. CoRR abs/2212.01897 (2022) - 2021
- [j38]Lucas Venezian Povoa, Uriel Cairê Balan Calvi, Ana Carolina Lorena, Carlos Henrique Costa Ribeiro, Israel T. da Silva:
A Multi-Learning Training Approach for Distinguishing Low and High Risk Cancer Patients. IEEE Access 9: 115453-115465 (2021) - [j37]Luiz Henrique dos Santos Fernandes, Ana Carolina Lorena, Kate Smith-Miles:
Towards Understanding Clustering Problems and Algorithms: An Instance Space Analysis. Algorithms 14(3): 95 (2021) - [j36]Leila Abuabara, Maria Gabriela Valeriano, Carlos Roberto Veiga Kiffer, Horacio Hideki Yanasse, Ana Carolina Lorena:
Using Machine Learning to support health system planning during the Covid-19 pandemic: a case study using data from São José dos Campos (Brazil). CLEI Electron. J. 24(3) (2021) - [j35]Victor H. Barella, Luís Paulo F. Garcia, Marcilio C. P. de Souto, Ana Carolina Lorena, André C. P. L. F. de Carvalho:
Assessing the data complexity of imbalanced datasets. Inf. Sci. 553: 83-109 (2021) - [j34]Mario Andrés Muñoz, Tao Yan, Matheus R. Leal, Kate Smith-Miles, Ana Carolina Lorena, Gisele L. Pappa, Rômulo Madureira Rodrigues:
An Instance Space Analysis of Regression Problems. ACM Trans. Knowl. Discov. Data 15(2): 28:1-28:25 (2021) - [c53]Luiz Henrique dos Santos Fernandes, Marcilio C. P. de Souto, Ana Carolina Lorena:
Evaluating Data Characterization Measures for Clustering Problems in Meta-learning. ICONIP (1) 2021: 621-632 - [c52]Adriano Rivolli, Luís Paulo F. Garcia, Ana Carolina Lorena, André C. P. L. F. de Carvalho:
A Study of the Correlation of Metafeatures Used for Metalearning. IWANN (1) 2021: 471-483 - [c51]Hério Sousa, Marcilio C. P. de Souto, Reginaldo Massanobu Kuroshu, Ana Carolina Lorena:
Automatic recovering the number k of clusters in the data by active query selection. SAC 2021: 1021-1029 - [i2]Pedro Yuri Arbs Paiva, Kate Smith-Miles, Maria Gabriela Valeriano, Ana Carolina Lorena:
PyHard: a novel tool for generating hardness embeddings to support data-centric analysis. CoRR abs/2109.14430 (2021) - 2020
- [j33]Luís Paulo F. Garcia, Adriano Rivolli, Edesio Alcobaça, Ana Carolina Lorena, André C. P. L. F. de Carvalho:
Boosting meta-learning with simulated data complexity measures. Intell. Data Anal. 24(5): 1011-1028 (2020) - [c50]José L. M. Arruda, Ricardo B. C. Prudêncio, Ana Carolina Lorena:
Measuring Instance Hardness Using Data Complexity Measures. BRACIS (2) 2020: 483-497 - [c49]Yuri Galindo, Marcelo De Cicco, Marcos G. Quiles, Ana Carolina Lorena:
Monitoring Night Skies with Deep Learning. ICONIP (4) 2020: 460-468
2010 – 2019
- 2019
- [j32]Ana Carolina Lorena, Luís Paulo F. Garcia, Jens Lehmann, Marcílio Carlos Pereira de Souto, Tin Kam Ho:
How Complex Is Your Classification Problem?: A Survey on Measuring Classification Complexity. ACM Comput. Surv. 52(5): 107:1-107:34 (2019) - [j31]Luís Paulo F. Garcia, Jens Lehmann, André C. P. L. F. de Carvalho, Ana Carolina Lorena:
New label noise injection methods for the evaluation of noise filters. Knowl. Based Syst. 163: 693-704 (2019) - [c48]Lucas P. Zorzi, Ana Carolina Lorena:
Exploring Artificial Neural Networks: A Data Complexity Perspective. BRACIS 2019: 830-835 - [c47]Lucas Chesini Okimoto, Ana Carolina Lorena:
Data complexity measures in feature selection. IJCNN 2019: 1-8 - 2018
- [j30]Thaise M. Quiterio, Ana Carolina Lorena:
Using complexity measures to determine the structure of directed acyclic graphs in multiclass classification. Appl. Soft Comput. 65: 428-442 (2018) - [j29]Paulo Henrique Pisani, Ana Carolina Lorena, André C. P. L. F. de Carvalho:
Adaptive Biometric Systems using Ensembles. IEEE Intell. Syst. 33(2): 19-28 (2018) - [j28]Ana Carolina Lorena, Aron I. Maciel, Péricles B. C. de Miranda, Ivan G. Costa, Ricardo B. C. Prudêncio:
Data complexity meta-features for regression problems. Mach. Learn. 107(1): 209-246 (2018) - [j27]Ana Carolina Lorena, Anne Magály de Paula Canuto:
Interdisciplinary Data Analysis. New Gener. Comput. 36(1): 1-3 (2018) - [c46]James Shiniti Nagai, Hério Sousa, Alexandre Hild Aono, Ana Carolina Lorena, Reginaldo Massanobu Kuroshu:
Gene Essentiality Prediction Using Topological Features From Metabolic Networks. BRACIS 2018: 91-96 - [c45]Guilherme Ribeiroda Silva, Márcio P. Basgalupp, Ana Carolina Lorena:
Automatic Design of Evolutionary Algorithms Based on Entropy Triggers. CEC 2018: 1-8 - [c44]Luís Paulo F. Garcia, Ana Carolina Lorena, Marcilio C. P. de Souto, Tin Kam Ho:
Classifier Recommendation Using Data Complexity Measures. ICPR 2018: 874-879 - [c43]Victor H. Barella, Luís Paulo F. Garcia, Marcilio C. P. de Souto, Ana Carolina Lorena, André C. P. L. F. de Carvalho:
Data Complexity Measures for Imbalanced Classification Tasks. IJCNN 2018: 1-8 - [c42]Vinícius Veloso de Melo, Ana Carolina Lorena:
Using Complexity Measures to Evolve Synthetic Classification Datasets. IJCNN 2018: 1-8 - [i1]Ana Carolina Lorena, Luís Paulo F. Garcia, Jens Lehmann, Marcilio C. P. de Souto, Tin Kam Ho:
How Complex is your classification problem? A survey on measuring classification complexity. CoRR abs/1808.03591 (2018) - 2017
- [j26]Newton Spolaôr, Ana Carolina Lorena, Huei Diana Lee:
Feature Selection via Pareto Multi-objective Genetic Algorithms. Appl. Artif. Intell. 31(9-10): 764-791 (2017) - [j25]Paulo Henrique Pisani, Norman Poh, André C. P. L. F. de Carvalho, Ana Carolina Lorena:
Score normalization applied to adaptive biometric systems. Comput. Secur. 70: 565-580 (2017) - [j24]Paulo Henrique Pisani, Ana Carolina Lorena, André C. P. L. F. de Carvalho:
Adaptive algorithms applied to accelerometer biometrics in a data stream context. Intell. Data Anal. 21(2): 353-370 (2017) - [j23]Pablo Morales-Álvarez, Julián Luengo, Luís Paulo F. Garcia, Ana Carolina Lorena, André C. P. L. F. de Carvalho, Francisco Herrera:
The NoiseFiltersR Package: Label Noise Preprocessing in R. R J. 9(1): 219 (2017) - [c41]Lucas Chesini Okimoto, Ricardo Manhães Savii, Ana Carolina Lorena:
Complexity Measures Effectiveness in Feature Selection. BRACIS 2017: 91-96 - [c40]Arua De M. Sousa, Ana Carolina Lorena, Márcio P. Basgalupp:
GEEK: Grammatical Evolution for Automatically Evolving Kernel Functions. TrustCom/BigDataSE/ICESS 2017: 941-948 - 2016
- [j22]Paulo Henrique Pisani, Romain Giot, André C. P. L. F. de Carvalho, Ana Carolina Lorena:
Enhanced template update: Application to keystroke dynamics. Comput. Secur. 60: 134-153 (2016) - [j21]Luís Paulo F. Garcia, Ana Carolina Lorena, Stan Matwin, André Carlos Ponce de Leon Ferreira de Carvalho:
Ensembles of label noise filters: a ranking approach. Data Min. Knowl. Discov. 30(5): 1192-1216 (2016) - [j20]Luís Paulo F. Garcia, André C. P. L. F. de Carvalho, Ana Carolina Lorena:
Noise detection in the meta-learning level. Neurocomputing 176: 14-25 (2016) - [c39]Thaise M. Quiterio, Ana Carolina Lorena:
Determining the Structure of Decision Directed Acyclic Graphs for Multiclass Classification Problems. BRACIS 2016: 115-120 - [c38]Aron I. Maciel, Ivan G. Costa, Ana Carolina Lorena:
Measuring the complexity of regression problems. IJCNN 2016: 1450-1457 - 2015
- [j19]Paulo Henrique Pisani, Ana Carolina Lorena:
Emphasizing typing signature in keystroke dynamics using immune algorithms. Appl. Soft Comput. 34: 178-193 (2015) - [j18]Luís Paulo F. Garcia, André C. P. L. F. de Carvalho, Ana Carolina Lorena:
Effect of label noise in the complexity of classification problems. Neurocomputing 160: 108-119 (2015) - [j17]Luiz Henrique Nogueira Lorena, André Carlos Ponce de Leon Ferreira de Carvalho, Ana Carolina Lorena:
Filter Feature Selection for One-Class Classification. J. Intell. Robotic Syst. 80(Supplement-1): 227-243 (2015) - [j16]Paulo Henrique Pisani, Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Adaptive Positive Selection for Keystroke Dynamics. J. Intell. Robotic Syst. 80(Supplement-1): 277-293 (2015) - [j15]Luís Paulo F. Garcia, José A. Sáez, Julián Luengo, Ana Carolina Lorena, André C. P. L. F. de Carvalho, Francisco Herrera:
Using the One-vs-One decomposition to improve the performance of class noise filters via an aggregation strategy in multi-class classification problems. Knowl. Based Syst. 90: 153-164 (2015) - [c37]Ana Carolina Lorena, Luís Paulo Faina Garcia, André C. P. L. F. de Carvalho:
Adapting Noise Filters for Ranking. BRACIS 2015: 299-304 - [c36]Paulo Henrique Pisani, Ana Carolina Lorena, André C. P. L. F. de Carvalho:
Ensemble of Adaptive Algorithms for Keystroke Dynamics. BRACIS 2015: 310-315 - [c35]Ana Carolina Lorena, Marcílio Carlos Pereira de Souto:
On Measuring the Complexity of Classification Problems. ICONIP (1) 2015: 158-167 - [c34]Jussara Dias, Marcos G. Quiles, Ana Carolina Lorena:
Using Growing Neural Gas in Prototype Generation for Nearest Neighbor Classifiers. ICONIP (2) 2015: 276-283 - [c33]Paulo Henrique Pisani, Ana Carolina Lorena, André C. P. L. F. de Carvalho:
Adaptive approaches for keystroke dynamics. IJCNN 2015: 1-8 - 2014
- [j14]Teresa Bernarda Ludermir, Cleber Zanchettin, Ana Carolina Lorena:
Advances in intelligent systems. Neurocomputing 127: 1-3 (2014) - [c32]Luiz Henrique Nogueira Lorena, Ana Carolina Lorena, Luiz Antonio Nogueira Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Clustering Search Applied to Rank Aggregation. BRACIS 2014: 198-203 - [c31]Paulo Henrique Pisani, Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Adaptive Algorithms in Accelerometer Biometrics. BRACIS 2014: 336-341 - 2013
- [j13]Paulo Henrique Pisani, Ana Carolina Lorena:
A systematic review on keystroke dynamics. J. Braz. Comput. Soc. 19(4): 573-587 (2013) - [c30]Luís Paulo F. Garcia, André C. P. L. F. de Carvalho, Ana Carolina Lorena:
Noisy Data Set Identification. HAIS 2013: 629-638 - 2012
- [j12]Paulo Henrique Pisani, Ana Carolina Lorena:
Comparison of Feature Vectors in Keystroke Dynamics: A Novelty Detection Approach. Int. J. Nat. Comput. Res. 3(4): 59-76 (2012) - [j11]Ana Carolina Lorena, Ivan G. Costa, Newton Spolaôr, Marcílio Carlos Pereira de Souto:
Analysis of complexity indices for classification problems: Cancer gene expression data. Neurocomputing 75(1): 33-42 (2012) - [c29]Paulo Henrique Pisani, Ana Carolina Lorena:
Evolutionary neural networks applied to keystroke dynamics: Genetic and immune based. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c28]Luís Paulo F. Garcia, Ana Carolina Lorena, André C. P. L. F. de Carvalho:
A Study on Class Noise Detection and Elimination. SBRN 2012: 13-18 - [c27]Paulo Henrique Pisani, Ana Carolina Lorena:
Negative Selection with High-Dimensional Support for Keystroke Dynamics. SBRN 2012: 19-24 - [e1]Ana Carolina Lorena, Carlos Eduardo Thomaz, Aurora Trinidad Ramirez Pozo:
2012 Brazilian Symposium on Neural Networks, Curitiba, Paraná, Brazil, October 20-25, 2012. IEEE Computer Society 2012, ISBN 978-1-4673-2641-4 [contents] - 2011
- [j10]Ana Carolina Lorena, Luís F. O. Jacintho, Marinez Ferreira de Siqueira, Renato De Giovanni, Lúcia G. Lohmann, André Carlos Ponce de Leon Ferreira de Carvalho, Missae Yamamoto:
Comparing machine learning classifiers in potential distribution modelling. Expert Syst. Appl. 38(5): 5268-5275 (2011) - [c26]Lucas Trambaiolli, Tiago H. Falk, Francisco J. Fraga, Renato Anghinah, Ana Carolina Lorena:
EEG spectro-temporal modulation energy: A new feature for automated diagnosis of Alzheimer's disease. EMBC 2011: 3828-3831 - [c25]Newton Spolaôr, Ana Carolina Lorena, Huei Diana Lee:
Multi-objective Genetic Algorithm Evaluation in Feature Selection. EMO 2011: 462-476 - 2010
- [j9]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Building binary-tree-based multiclass classifiers using separability measures. Neurocomputing 73(16-18): 2837-2845 (2010) - [c24]Marcílio Carlos Pereira de Souto, Ana Carolina Lorena, Newton Spolaôr, Ivan Gesteira Costa:
Complexity measures of supervised classifications tasks: A case study for cancer gene expression data. IJCNN 2010: 1-7 - [c23]Ana Carolina Lorena, Newton Spolaôr, Ivan G. Costa, Marcilio C. P. de Souto:
On the Complexity of Gene Marker Selection. SBRN 2010: 85-90 - [c22]Newton Spolaôr, Ana Carolina Lorena, Huei Diana Lee:
Use of Multiobjective Genetic Algorithms in Feature Selection. SBRN 2010: 146-151 - [c21]Francisco de Assis Zampirolli, Beatriz Stransky, Ana Carolina Lorena, Fábio Luis de Melo Paulon:
Segmentation and Classification of Histological Images - Application of Graph Analysis and Machine Learning Methods. SIBGRAPI 2010: 331-338 - [p3]Hugo L. Borges, Ana Carolina Lorena:
A Survey on Recommender Systems for News Data. Smart Information and Knowledge Management 2010: 129-151
2000 – 2009
- 2009
- [j8]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Evaluation Functions for the Evolutionary Design of Multiclass Support Vector Machines. Int. J. Comput. Intell. Appl. 8(1): 53-68 (2009) - [j7]Giampaolo L. Libralon, André Carlos Ponce de Leon Ferreira de Carvalho, Ana Carolina Lorena:
Pre-processing for noise detection in gene expression classification data. J. Braz. Comput. Soc. 15(1): 3-11 (2009) - [c20]André L. B. Miranda, Luís Paulo F. Garcia, André C. P. L. F. de Carvalho, Ana Carolina Lorena:
Use of Classification Algorithms in Noise Detection and Elimination. HAIS 2009: 417-424 - [c19]Ivan G. Costa, Ana Carolina Lorena, Liciana R. M. P. y Peres, Marcílio Carlos Pereira de Souto:
Using Supervised Complexity Measures in the Analysis of Cancer Gene Expression Data Sets. BSB 2009: 48-59 - 2008
- [j6]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho, João Gama:
A review on the combination of binary classifiers in multiclass problems. Artif. Intell. Rev. 30(1-4): 19-37 (2008) - [j5]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Evolutionary tuning of SVM parameter values in multiclass problems. Neurocomputing 71(16-18): 3326-3334 (2008) - [j4]Ana Carolina Lorena, André C. P. L. F. de Carvalho:
Estratégias para a Combinação de Classificadores Binários em Soluções Multiclasses. RITA 15(2): 65-86 (2008) - [c18]Ana Carolina Lorena, Ivan G. Costa, Marcílio Carlos Pereira de Souto:
On the Complexity of Gene Expression Classification Data Sets. HIS 2008: 825-830 - [c17]Giampaolo L. Libralon, André Carlos Ponce de Leon Ferreira de Carvalho, Ana Carolina Lorena:
Ensembles of Pre-processing Techniques for Noise Detection in Gene Expression Data. ICONIP (1) 2008: 486-493 - [c16]Ana Carolina Lorena, Marinez Ferreira de Siqueira, Renato De Giovanni, André Carlos Ponce de Leon Ferreira de Carvalho, Ronaldo C. Prati:
Potential Distribution Modelling Using Machine Learning. IEA/AIE 2008: 255-264 - [c15]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Tree Decomposition of Multiclass Problems. SBRN 2008: 189-194 - [c14]Eduardo P. Costa, Ana Carolina Lorena, André C. P. L. F. de Carvalho, Alex Alves Freitas:
Top-Down Hierarchical Ensembles of Classifiers for Predicting G-Protein-Coupled-Receptor Functions. BSB 2008: 35-46 - [c13]Willian Zalewski, Huei Diana Lee, Adewole M. J. F. Caetano, Ana Carolina Lorena, André Gustavo Maletzke, João José Fagundes, Cláudio Saddy Rodrigues Coy, Feng Chung Wu:
Evaluation of Models for the Recognition of Hadwritten Digits in Medical Forms. BSB 2008: 178-181 - [p2]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Investigation of Strategies for the Generation of Multiclass Support Vector Machines. New Challenges in Applied Intelligence Technologies 2008: 319-328 - [p1]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
evolutionary Design of Code-matrices for Multiclass Problems. Soft Computing for Knowledge Discovery and Data Mining 2008: 153-184 - 2007
- [j3]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Protein cellular localization prediction with Support Vector Machines and Decision Trees. Comput. Biol. Medicine 37(2): 115-125 (2007) - [j2]Ana Carolina Lorena, André C. P. L. F. de Carvalho:
Evolutionary design of multiclass support vector machines. J. Intell. Fuzzy Syst. 18(5): 445-454 (2007) - [j1]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Uma Introdução às Support Vector Machines. RITA 14(2): 43-67 (2007) - [c12]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Comparing Several Evaluation Functions in the Evolutionary Design of Multiclass Support Vector Machines. HIS 2007: 53-58 - [c11]Eduardo P. Costa, Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho, Alex Alves Freitas, Nicholas Holden:
Comparing Several Approaches for Hierarchical Classification of Proteins with Decision Trees. BSB 2007: 126-137 - 2006
- [b1]Ana Carolina Lorena:
Investigation of strategies for the generation of multiclass support vector machines. University of São Paulo, Brazil, 2006 - [c10]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Multiclass SVM Design and Parameter Selection with Genetic Algorithms. SBRN 2006: 131-136 - 2005
- [c9]Daniela Mayumi Ushizima, Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Support Vector Machines Applied to White Blood Cell Recognition. HIS 2005: 379-384 - [c8]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Minimum Spanning Trees in Hierarchical Multiclass Support Vector Machines Generation. IEA/AIE 2005: 422-431 - [c7]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Protein Cellular Localization with Multiclass Support Vector Machines and Decision Trees. BSB 2005: 42-53 - 2004
- [c6]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Comparing Techniques for Multiclass Classification Using Binary SVM Predictors. MICAI 2004: 272-281 - [c5]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
An Hybrid GA/SVM Approach for Multiclass Classification with Directed Acyclic Graphs. SBIA 2004: 366-375 - 2003
- [c4]Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho:
Human Splice Site Identification with Multiclass Support Vector Machines and Bagging. ICANN 2003: 234-244 - 2002
- [c3]Ana Carolina Lorena, Gustavo E. A. P. A. Batista, André Carlos Ponce de Leon Ferreira de Carvalho, Maria Carolina Monard:
The Influence of Noisy Patterns in the Performance of Learning Methods in the Splice Junction Recognition Problem. SBRN 2002: 31-37 - [c2]Ana Carolina Lorena, Gustavo E. A. P. A. Batista, André Carlos Ponce de Leon Ferreira de Carvalho, Maria Carolina Monard:
Splice Junction Recognition using Machine Learning Techniques. WOB 2002: 32-39 - [c1]Silvia H. M. G. da Silva, Ana Carolina Lorena, André Carlos Ponce de Leon Ferreira de Carvalho, Danielle D. Tambasco, Luciana C. A. Regitano:
Aprendizado de Máquina Aplicado ao Estudo de Marcadores Moleculares para Produção de Carne Bovina. WOB 2002: 105-107
Coauthor Index
André C. P. L. F. de Carvalho
aka: André Carlos Ponce de Leon Ferreira de Carvalho
aka: André Carlos Ponce de Leon Ferreira de Carvalho
Luís Paulo F. Garcia
aka: Luís Paulo Faina Garcia
aka: Luís Paulo Faina Garcia
Marcílio Carlos Pereira de Souto
aka: Marcilio C. P. de Souto
aka: Marcilio C. P. de Souto
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