1. Research on Bayesian decision theory based relevance feedback mechanism.

2. Combined with statistical based Bayesian estimation and adaptive distribution parameter estimation, an effective denoising algorithm is gained.

3. Psychologically, people tend to be Bayesian — to the extent of often making false connections.http://

4. To thoroughly understand the Bayesian network methodology, we start with the basic ideas of Bayes' Theorem and empirical Bayes method along with some illustrating examples.

5. Then, based on the Bayesian theorem, sample likelihood function and priori distribution of the model, the posteriori distribution of parameters was derived.

6. On the customer support side, a Bayesian Filtering algorithm zaps spam and turns email into trackable cases routed to the correct department.

7. Traditionally, we solve a general Bayesian decision problem by using the decision tree analysis method.

8. It discusses the rationale and principle of Bayesian spectrum analysis, studies and calculates the frequency scanning method and the frequency difference scanning method respectively.

9. Bayesian network is one of the most efficient models in the uncertain knowledge and reasoning field.

10. In PS ALT, we obtain the Bayesian estimation of each parameter and marginal posterior density when the prior density of shape parameter is continuous using Laplace method under CE model.

11. Bayesian inference has also gained prominence in e-mail spam-fighting, and in non-spam-related areas such as customer affinity engines (or, commercial recommendation engines).

12. Firstly, the bottleneck of actual Bayesian expert system classifier was identified according to the process analysis.

13. Bayesian classification and the back of the linear, non - linear classifier belong to supervised learning.

14. A modified approach to combine the Bayesian estimation and the hard gating is proposed.

15. Dynamic Bayesian planning graph adds dynamic Bayesian inference to based planning graph. It represents system security states explicitly and the relation between states and actions.

16. Bayesian decision theory as part of the modern inductive logic has had a great influence on the development of inductive logic.

17. An estimation method of system reliability based on Bayesian statistical theory is presented in consideration of the uncertainty of component reliability estimates for distributed monitoring systems.

18. Bayesian decision theory is widely used in pattem recognition and signal detection.

19. Statistical inversion of seafloor parameters based on Bayesian inference is an interesting topic in the research of underwater acoustics.

20. The resulting type of statistical methodology is known as Bayesian, and is still controversial.

21. The image denoising method is proposed based on dual tree complex wavelet transform and Bayesian estimation.

22. And the values of recessive allele and some parameters of genetic diversity were also quite different using the square root method and the Bayesian method.

23. With respect to the small sample size of some ships, this paper presents a Bayesian method for selecting the ship-board repair parts and spares.

24. For a foggy input image, there is a clear image correspondingly. The Bayesian framework is established using the maximum probability of the corresponding clear image appearing for a given foggy image.

25. Then, it is revised and regulated based on basic dependency relationship between variables, basic structure between nodes and dependency analysis method to obtain a new Bayesian network structure.

26. Complexity of BN reasoning systems relies on probability table-scale corresponding to SBN(sub- Bayesian network) decomposed, namely attribute variable-scale of probability table and value states.

27. But because of their philosophical training in the rigours of Pascal's method, the Bayesian bolt-on does not come easily to scientists.

28. Mahout currently supports two related approaches to categorizing/classifying content based on bayesian statistics.

29. For the life data X in a life test, the Bayesian stopping rule and decision rule for the problem of testing fuzzy statistical hypotheses is given in this paper.

30. The article introduces a kind of images restoration method, which make use of relative characters of image pixels, and combines genetic algorithms inducting line process with Bayesian estimation.

31. According to Bayesian theory and Bayes Factor, the posterior probability of the calculation sample belonging to a model is calculated.

32. However, reasoning on student model is a NP hard question in fact, since undirected loops are embedded in the Bayesian student model.

33. Under the assumption of security dependence relation among different network nodes, a Bayesian model is put forward for locating and tracing a network attack.

33. Wish you can benefit from our online sentence dictionary and make progress every day!

34. Bayesian more of mouthwash will help to keep the mouth clean.

35. A dual isomorphic Bayesian network model for medium voltage distribution system reliability re - assessment is also proposed.

36. The foundation of Bayesian decision theory is how to represent our values and beliefs.

37. The corresponding nonlinear threshold functions (bivariate shrinkage function) are derived from the model using the Bayesian estimation theory.

38. The paper introduces the target tracking algorithms based on Bayesian inference, which can be applied in the systems of nonlinearity and non-Gaussianity.

39. Bayesian network and Boolean network are powerful tools to genetic networks research.

40. Secondly, this thesis discusses the method of applying Bayesian Network inferring mechanism to educational hypermedia system.

41. The Bayesian estimation is derived through statistical analysis and it is shown to be equivalent to the maximization of the a Posteriori Probability.

42. Both likelihood ratio tests and Bayesian inference are employed to study the phylogeny of Phasianidae.

43. Two Bayesian network and Markov network structure learning methods are presented.

44. An image denoising method is proposed based on dual tree complex wavelet transform and Bayesian estimation.

45. The model can predict and decide to overcome the shortcomings of Bayesian reliability growth models.

46. An assessment technique that assesses vehicle dynamic performance using the data of rail measurement was developed by Bayesian estimation principle.

47. On the backdrop of electronic reconnaissance and infrared photographic reconnaissance, we develop a multisensor target identification system based on Bayesian Networks.

48. Beginning with the analysis of the Uncertainty in hypermedia system, the paper introduces the Bayesian networks.

49. Bayesian decision theory as part of the modern inductive logic has had a great influence logic.

50. We use Bayesian maximum a posteriori estimation training a speaker model from background model, to solve the problem of model miss matching in speaker verification system.

51. Bayesian estimation of parameters and index of reliability from two-parameter exponential distribution under time curtailed test were given.

52. Bayesian inference treats model parameters as random variables whereas frequentist inference considers them to be estimates of fixed, 'true' quantities.

53. Simultaneousty, the parameters, hyper parameters and model parameters at the other levels keep unchanged to simplify the parameters estimation of Bayesian feed forward networks.

54. RESULTS: This method can be used as variance analysis and data processing of Bayesian statistics evalustion.

55. Furthermore, prior probability of each knowledge point is determined by the directed acyclic graph based on knowledge points, and Bayesian Network based on knowledge points is built.

56. The results shows that the Bayesian Belief Network has better performance than the Decision Tree and Support Vector Machine.

57. Influence Diagrams(IDs) are graphical knowledge representation of decision problems and can be viewed as an extension of Bayesian Networks(BNs) with additional node types for decision and utility.

58. For example, we construct GPS and PPSP for phosphorylation site prediction, based on GPS and Bayesian Decision Theory algorithms, respectively.

59. The effect of informational external representation on Bayesian reasoning was studied from the perspective of distributed cognition.

60. Particle filter is a new real time inference algorithm, which is based on Bayesian inference and Monte Carlo method.

61. Decision theory, statistical classification, maximum likelihood and Bayesian estimation, non - parametric methods, unsupervised learning and clustering.

62. It proposed the improvement Bayesian sorting algorithm by the foundation of the empirical data.

63. Kalman-Filter-based optimal observation scheme is a Bayesian method,(Sentence dictionary) which improves observation locations by minimizing the expectation of the root mean square deviation(RMSD) of the analysis field.

64. Then parameters of the cost - sensitivity Bayesian networks are evaluated based on cost - sensitivity loss function.

65. To improve the accuracy and speed in cycle-accurate power estimation, this paper uses multiple dimensional coefficients to build a Bayesian inference dynamic power model.

66. The type and parameters of the prior data distribution should be known in Bayesian method.

67. The paper presents a kind of bayesian inference of simple signal in dynamic measurement. The simple measured signals and output signals are thought of as realizations of stochastic process.

68. By using a data set comprising mitochondrial genomes from 177 humans, we estimate substitution rates for various data partitions by using Bayesian phylogenetic analysis with a relaxed molecular clock.

69. In addition, the multiple fuzzy hypothesis testing is studied from the Bayesian statistical viewpoint.

70. The Bayesian classification technique which is relatively more mature in field of fuzzy recognition is applied to the detection technique of P2P deep flow inspection.

71. Objective To investigate the accuracy of Bayesian fitting for predicting aminoglycoside concentrations using Abbottbase pharmacokinetic systems program (PKS).

72. Under the law of maximum shoddy probability, it will have more practical significance for the probabilistic analysis of degree of compaction to use decision analysis and Bayesian method.

73. In Bayesian reference, marginal likelihood function involve to compute high dimensional complex integrand. So exactly to compute marginal likelihood is often difficult.

74. Upon this frame, use matrix Lie group to express the rotation space, then base on Bayesian estimation framework, calculate the minimum mean squared error bounds which use the matrix Lie groups.

75. Based on wavelet domain Hidden Markov model, a novel speckle suppression method for medical ultrasound images is presented which combines Bayesian estimation and homomorphic filtering.

76. The algorithms used in maneuvering target tracking can be classified as methods based on maximum likelihood estimation and methods based on Bayesian estimation.

77. This paper describes a methodology based on ILP for upgrading na ? ve Bayesian classifiers to first-order logic.

78. In this paper, the conditional mean and its applications to Bayesian estimation of the parameters and reliability measures of weibull distribition and power-law process are discussed.

79. Monte Carlo method is used to sample geophysical model according to Bayesian inference.

80. Modeling with Bayesian belief network has been a powerful tool to solve many uncertainty problems.

81. Through the analysis of the composite base price and the introduction to the Bayesian decision, the Bayes theorem is led into determining the quoted price with the composite base price.

82. Bayesian Belief Network(BBN)is a graphic model that encodes joint probability distribution among uncertain variables, it express a potential dependent relationship between variables.

83. Confidence intervals play a similar role in frequentist statistics to the credibility interval in Bayesian statistics.

84. The method is to derive the maximum a posteriori estimate of the regions and the boundaries by using Bayesian inference and neighborhood constraints based on Markov random fields(MRFs) models.

85. It is seen that hierarchical Bayesian estimation is more efficient than maximum likelihood estimation through Monte Carlo simulation and an example.

86. Then we employ Bayesian classifier to classify these questions. Answer extraction is the most crucial part for question answering system.

87. Bayesian neural network, each error value and the right to be treated as random variables, and their apriori probability distribution is the normal distribution.

88. The most common statistical approach is called bayesian inference and is explained in detail in another IBM developerWorks article (see Resources).

89. Then the optimal estimation of the object state parameters is obtained by Bayesian inference.

90. Geller et al. 122 proposed that the question of precursor test can be addressed using a Bayesian approach where each failed attempt at prediction lowers the apriori probability for the next attempt.

91. Finally, the software was made, in the VC program environment, about the emulation mode of combine the situation assessment and threat estimate with the Bayesian net.

92. Fifthly, A risk analysis implementation flow based on Bayesian Networks(BNs) for risk analysis module is presented. In addition, the BNs is applied to risk analysis module of a real case.

93. With the development of the Bayesian networks on knowledge representation and reasoning algorithms, the methods for SA based on the BNs technology become a hot topic in the domain of SA.

94. The principle of Recursive Bayesian estimation was introduced which was the basis of Particle filter, and the significance of importance function to the design of particle filter was illustrated.

95. We adopt a way of attribute selection based on word entropy, use vectors which are represented by word frequency, and deduce its corresponding Bayesian formula.

96. The purpose of this paper is to summary the literatures on tests of portfolio mean-variance efficiency in the framework of classical statistics and Bayesian inference.

97. The results show that the Bayesian method is capable of handling both statistical uncertainty and fatigue fun-outs.

98. Then we will introduce some common-used filtering techniques. Particle filter which is based on Bayesian estimation and Monte Carlo method will be emphasized.

99. Two different global localization methods based on Bayesian estimation theory are investigated in the paper.

100. A risk evaluation model in software project investment based on Bayesian Networks(BNs) is presented in this paper.

101. BFS ( Bayesian Forecasting System ) is one of theoretic frames to produce probabilistic hydrological forecasts.

102. The applicability of third-part test process is illustrated as Bayesian Nash Equilibrium of the compound strategies game model, and a discussion on cooperation possibility is made with Shapley value.

103. It is mainly of two kinds, Naive Bayesian Classification and Bayesian Belief Network Classification.

104. We review the basic principle, formalism, and philosophy of Bayesian inference and discuss its application in the context of the analytic continuation problem.

105. In random environment, a measuring model based on Bayesian estimation is given. In this model, prior distribution is obtained through conjugate law.

106. Then the image noises are removed using Bayesian estimation, producing the preliminary denoised image after reconstruction.

107. This paper builds a Bayesian inference network model based on the Rough Sets and Reason Rules and apply it to fulfill the medical data mining work.

108. Methods of GM(1,1) gray prediction, Bayesian and antecedence index were employed.

109. To solve localization problems of autonomous robots, self-localization methods based on Bayesian filter theory are investigated.

110. Bayesian network is a powerful knowledge representation for decomposing joint probability ( or probability density ).

111. Two different global localization methods based on Bayesian estimation theory are mainly investigated in the paper.

112. Chapter 2 gives an overview on Bayesian decision theory firstly. To overcome the weakness of MLE, we bring discriminative training methods for hidden Markov models into speech evaluation system.

113. Finally, calculations of simulations are performed, which show that the expected Bayesian estimation method is feasible and easy to operate.

114. A probability model based on Bayesian principles is given to measure the semantic association from a concept to its direct-related concept in domain ontology.

115. In this paper, the Bayesian sequential estimation of the parameter about acceptance test of products is studied.

116. Bayesian reliability sequential testing method is gave out for exponential distribution.

117. Bayesian feedback cloud model is constructed with the combination of human being's apriority and feature of cloud model.

118. If Bayesian inference used to describe the problem, the posterior probability density function of earth model describes the solution of a geophysical inverse problem.

119. Based on finite mixture models, we apply Bayesian method to compositional data and ordinal data clustering.

120. The algorithm handles uncertain information with Bayesian inference, giving a quantitative evaluation of the security state of a system and eliminating false alarms effectively.

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