Results 21 to 30 of about 35,767 (304)
Targeting: Logistic Regression, Special Cases and Extensions
ISPRS International Journal of Geo-Information, 2014 Logistic regression is a classical linear model for logit-transformed conditional probabilities of a binary target variable. It recovers the true conditional probabilities if the joint distribution of predictors and the target is of log-linear form ...
Helmut Schaeben
doaj +1 more source
Undirected Structural Markov Property for Bayesian Model Determination
Mathematics, 2023 This paper generalizes the structural Markov properties for undirected decomposable graphs to arbitrary ones. This helps us to exploit the conditional independence properties of joint prior laws to analyze and compare multiple graphical structures, while
Xiong Kang, Yingying Hu, Yi Sun
doaj +1 more source
Bayesian Test of Significance for Conditional Independence: The Multinomial Model
Entropy, 2014 Conditional independence tests have received special attention lately in machine learning and computational intelligence related literature as an important indicator of the relationship among the variables used by their models.
Pablo de Morais Andrade +2 more
doaj +1 more source
Online Streaming Feature Selection via Conditional Independence
Applied Sciences, 2018 Online feature selection is a challenging topic in data mining. It aims to reduce the dimensionality of streaming features by removing irrelevant and redundant features in real time.
Dianlong You +7 more
doaj +1 more source
IEEE Access, 2022 In the field of speaker verification (SV), the development of noise-robust systems is a challenge for their deployment in real-world environments. Noise variability compensation is a common strategy for increasing the robustness to noise variations.
Sunghyun Yoon
doaj +1 more source
Minimax optimal conditional independence testing [PDF]
The Annals of Statistics, 2021 We consider the problem of conditional independence testing of $X$ and $Y$ given $Z$ where $X,Y$ and $Z$ are three real random variables and $Z$ is continuous. We focus on two main cases - when $X$ and $Y$ are both discrete, and when $X$ and $Y$ are both continuous.
Neykov, Matey +2 more
openaire +2 more sources
Conditional Independence in Statistics [PDF]
, 2010 The theory of conditional independence is explained and the relations between ancillarity, sufficiency, and statistical independence are discussed in depth. Some related concepts like specific sufficiency, bounded completeness, and splitting sets are also studied in some details by using the language of conditional independence.
Basu, D., Pereira, Carlos A. B.
openaire +2 more sources
Complexity as Causal Information Integration
Entropy, 2020 Complexity measures in the context of the Integrated Information Theory of consciousness try to quantify the strength of the causal connections between different neurons.
Carlotta Langer, Nihat Ay
doaj +1 more source
Nonparametric conditional local independence testing [PDF]
The Annals of Statistics, 2023 62 pages, 10 figures.
Christgau, Alexander Mangulad +2 more
openaire +3 more sources
Optimizing Epistemic Model Checking Using Conditional Independence (Extended Abstract) [PDF]
Electronic Proceedings in Theoretical Computer Science, 2017 This paper shows that conditional independence reasoning can be applied to optimize epistemic model checking, in which one verifies that a model for a number of agents operating with imperfect information satisfies a formula expressed in a modal multi-
Ron van der Meyden
doaj +1 more source