TY - GEN
T1 - Approximation by Filter Functions
AU - Düntsch, Ivo
AU - Gediga, Günther
AU - Wang, Hui
PY - 2018/8/15
Y1 - 2018/8/15
N2 - In this exploratory article, we draw attention to the common formal ground among various estimators such as the belief functions of evidence theory and their relatives, approximation quality of rough set theory, and contextual probability. The unifying concept will be a general filter function composed of a basic probability and a weighting which varies according to the problem at hand. To compare the various filter functions we conclude with a simulation study with an example from the area of item response theory.
AB - In this exploratory article, we draw attention to the common formal ground among various estimators such as the belief functions of evidence theory and their relatives, approximation quality of rough set theory, and contextual probability. The unifying concept will be a general filter function composed of a basic probability and a weighting which varies according to the problem at hand. To compare the various filter functions we conclude with a simulation study with an example from the area of item response theory.
U2 - 10.1007/978-3-319-99368-3_19
DO - 10.1007/978-3-319-99368-3_19
M3 - Conference contribution
VL - 11103
T3 - Lecture Notes in Computer Science
SP - 243
EP - 256
BT - Lecture Notes in Computer Science
PB - Springer
ER -