@incollection{fdi:010055254,
  title = {{S}upervised feature evaluation by consistency analysis : application to measure sets used to characterise geographic objects},
  author = {{T}aillandier, {P}. and {D}rogoul, {A}lexis},
  editor = {},
  language = {{ENG}},
  abstract = {{N}owadays, supervised learning is commonly used in many domains. {I}ndeed, many works propose to learn new knowledge from examples that translate the expected behaviour of the considered system. {A} key issue of supervised learning concerns the description language used to represent the examples. {I}n this paper, we propose a method to evaluate the feature set used to describe them. {O}ur method is based on the computation of the consistency of the example base. {W}e carried out a case study in the domain of geomatic in order to evaluate the sets of measures used to characterise geographic objects. {T}he case study shows that our method allows to give relevant evaluations of measure sets},
  keywords = {{INTELLIGENCE} {ARTIFICIELLE} ; {SYSTEME} {D}'{INFORMATION} {GEOGRAPHIQUE} ; {GEOMATIQUE} ; {COHERENCE}},
  booktitle = {{S}econd international conference on knowledge and systems engineering : proceedings},
  numero = {},
  pages = {63--68},
  address = {{N}ew {Y}ork},
  publisher = {{IEEE}},
  series = {{IEEE} {C}onference {P}ublications},
  year = {2010},
  DOI = {10.1109/{KSE}.2010.28},
  ISBN = {978-1-4244-8334-1},
  URL = {https://www.documentation.ird.fr/hor/fdi:010055254},
}