( en | de | ru )

 

Disambiguation of "Sáez, José A."

Author of the publication

copydeleteadd this publication to your clipboard
Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness.

, , , and . Inf. Sci., (2013)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Rodrigo Sáez Araoz

Chemical bath deposition of Zn(S,O) buffer layers and application in Cd-free chalcopyrite based thin film solar cells and modules. FU Berlin, (2009)

Julio Sáez Rodríguez

Rosa Sáez Díaz

Jorge Rafael Sáez Paz

Patricio Sáez Briones

 

Other publications of authors with the same name

SRCS: Statistical Ranking Color Scheme for Visualizing Parameterized Multiple Pairwise Comparisons with R., and . R J., 7 (2): 89 (2015)Tackling the problem of noisy IoT sensor data in smart agriculture: Regression noise filters for enhanced evapotranspiration prediction., , and . Expert Syst. Appl., 237 (Part B): 121608 (March 2024)Managing Borderline and Noisy Examples in Imbalanced Classification by Combining SMOTE with Ensemble Filtering., , , and . IDEAL, volume 8669 of Lecture Notes in Computer Science, page 61-68. Springer, (2014)Fuzzy Rule Based Classification Systems versus crisp robust learners trained in presence of class noise's effects: A case of study., , and . ISDA, page 1229-1234. IEEE, (2011)On the suitability of stacking-based ensembles in smart agriculture for evapotranspiration prediction., , and . Appl. Soft Comput., (2021)Dataset Weighting via Intrinsic Data Characteristics for Pairwise Statistical Comparisons in Classification., , and . HAIS, volume 11734 of Lecture Notes in Computer Science, page 61-72. Springer, (2019)Tackling label noise with multi-class decomposition using fuzzy one-class support vector machines., , and . FUZZ-IEEE, page 915-922. IEEE, (2016)ANCES: A novel method to repair attribute noise in classification problems., and . Pattern Recognit., (2022)KSUFS: A Novel Unsupervised Feature Selection Method Based on Statistical Tests for Standard and Big Data Problems., and . IEEE Access, (2019)Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness., , , and . Inf. Sci., (2013)