FPD confirmation measures are used in ranking inductive rules in Data Mining. Many measures of this kind have been defined in literature. We show how some of them are related to each other via weighted means. The special structure of IFPD measures allows to define also new monotonicity and symmetry properties which appear quite natural in such context. We also suggest a way to measure the degree of symmetry of IFPD confirmation measures
In many problems in science and engineering ranging from astrophysics to geosciences to financial an...
AbstractIn many realistic problem domains, the main variable of interest behaves monotonically in th...
We introduce a new "Monotonic Imbalance Bounding" (MIB) class of matching methods for causal inferen...
FPD confirmation measures are used in ranking inductive rules in Data Mining. Many measures of this ...
Abstract. We investigate a monotone link between Bayesian confirma-tion measures and rule support an...
While Bayesian Confirmation Measures assess the degree to which an antecedent E supports a conclusio...
Many Bayesian Confirmation Measures have been proposed so far. They are used to assess the degree to...
Bayesian Confirmation Measures (BCMs) are used to assess the degree to which an evidence (or premise...
Bayesian Confirmation Measures are used to assess the de- gree to which an evidence E supports or co...
This dissertation studies the incorporation of monotonicity constraints as a type of domain knowledg...
Bayesian Confirmation Measures (BCMs) assess the impact of the occurrence of one event on the credib...
According to a widespread but implicit thesis in Bayesian confirmation theory, two confirmation meas...
For many real-life Bayesian networks, common knowledge dictates that the output established for the ...
For many real-life Bayesian networks, common knowledge dictates that the output established for the ...
Problem statement: When analyzing random variables it was useful to measure the degree of their mono...
In many problems in science and engineering ranging from astrophysics to geosciences to financial an...
AbstractIn many realistic problem domains, the main variable of interest behaves monotonically in th...
We introduce a new "Monotonic Imbalance Bounding" (MIB) class of matching methods for causal inferen...
FPD confirmation measures are used in ranking inductive rules in Data Mining. Many measures of this ...
Abstract. We investigate a monotone link between Bayesian confirma-tion measures and rule support an...
While Bayesian Confirmation Measures assess the degree to which an antecedent E supports a conclusio...
Many Bayesian Confirmation Measures have been proposed so far. They are used to assess the degree to...
Bayesian Confirmation Measures (BCMs) are used to assess the degree to which an evidence (or premise...
Bayesian Confirmation Measures are used to assess the de- gree to which an evidence E supports or co...
This dissertation studies the incorporation of monotonicity constraints as a type of domain knowledg...
Bayesian Confirmation Measures (BCMs) assess the impact of the occurrence of one event on the credib...
According to a widespread but implicit thesis in Bayesian confirmation theory, two confirmation meas...
For many real-life Bayesian networks, common knowledge dictates that the output established for the ...
For many real-life Bayesian networks, common knowledge dictates that the output established for the ...
Problem statement: When analyzing random variables it was useful to measure the degree of their mono...
In many problems in science and engineering ranging from astrophysics to geosciences to financial an...
AbstractIn many realistic problem domains, the main variable of interest behaves monotonically in th...
We introduce a new "Monotonic Imbalance Bounding" (MIB) class of matching methods for causal inferen...