An explication of uncertain evidence in Bayesian networks: Likelihood evidence and probabilistic evidence: Uncertain evidence in Bayesian networks
This paper proposes a systematized presentation and a terminology for observations in a
Bayesian network. It focuses on the three main concepts of uncertain evidence, namely …
Bayesian network. It focuses on the three main concepts of uncertain evidence, namely …
Paid: A probabilistic agent-based intrusion detection system
In this paper we describe architecture and implementation of a Probabilistic Agent-Based
Intrusion Detection (PAID) system. The PAID system has a cooperative agent architecture …
Intrusion Detection (PAID) system. The PAID system has a cooperative agent architecture …
Inference in possibilistic network classifiers under uncertain observations
S Benferhat, K Tabia - Annals of Mathematics and Artificial Intelligence, 2012 - Springer
Possibilistic networks, which are compact representations of possibility distributions, are
powerful tools for representing and reasoning with uncertain and incomplete information in …
powerful tools for representing and reasoning with uncertain and incomplete information in …
Jeffrey's rule of conditioning in a possibilistic framework: an analysis of the existence and uniqueness of the solution
S Benferhat, K Tabia, K Sedki - Annals of Mathematics and Artificial …, 2011 - Springer
Conditioning, belief update and revision are important tasks for designing intelligent
systems. Possibility theory is among the powerful uncertainty theories particularly suitable …
systems. Possibility theory is among the powerful uncertainty theories particularly suitable …
Understanding soft evidence as probabilistic evidence: Illustration with several use cases
This paper aims to get a better understanding of the notions of evidence, probabilistic
evidence and likelihood evidence in Bayesian Networks. Evidence comes from an …
evidence and likelihood evidence in Bayesian Networks. Evidence comes from an …
Ensuring the integrity and interoperability of educational usage and social data through Caliper framework to support competency-assessment
A Rayon, M Guenaga, A Nunez - 2014 IEEE Frontiers in …, 2014 - ieeexplore.ieee.org
The acquisition of knowledge is no longer enough to succeed in a society characterized by a
constant change and high levels of uncertainty. Accordingly, universities have increasingly …
constant change and high levels of uncertainty. Accordingly, universities have increasingly …
Performance evaluation of algorithms for soft evidential update in Bayesian networks: First results
S Langevin, M Valtorta - … Conference, SUM 2008, Naples, Italy, October 1 …, 2008 - Springer
In this paper we analyze the performance of three algorithms for soft evidential update, in
which a probability distribution represented by a Bayesian network is modified to a new …
which a probability distribution represented by a Bayesian network is modified to a new …
Unsupervised co-training of Bayesian networks for condition prediction
Abstract The objective of Smart Manufacturing is to improve productivity and
competitiveness in industry, based on in-process data. It requires reliable, explainable and …
competitiveness in industry, based on in-process data. It requires reliable, explainable and …
From information to evidence in a bayesian network
Evidence in a Bayesian network comes from information based on the observation of one or
more variables. A review of the terminology leads to the assessment that two main types of …
more variables. A review of the terminology leads to the assessment that two main types of …
Observations probabilistes dans les réseaux bayésiens
AB Mrad - 2015 - theses.hal.science
Dans un réseau bayésien, une observation sur une variable signifie en général que cette
variable est instanciée. Ceci signifie que l'observateur peut affirmer avec certitude que la …
variable est instanciée. Ceci signifie que l'observateur peut affirmer avec certitude que la …