TY  - GEN 
AU  - Sáez Muñoz, José Antonio
PY  - 2023
UR  - https://hdl.handle.net/10481/81835
AB  - Classification datasets created from chemical processes can be affected by
errors, which impair the accuracy of the models built. This fact highlights the
importance of analyzing the robustness of classifiers against different types
and levels of...
LA  - eng
PB  - Wiley
KW  - Attribute noise
KW  - Chemical data
KW  - Classification
KW  - Label noise
KW  - Noise models
TI  - Noise simulation in classification with the noisemodel R package: Applications analyzing the impact of errors with chemical data
DO  - 10.1002/cem.3472
ER  -