Examples of using Bayesian in English and their translations into Arabic
{-}
-
Colloquial
-
Political
-
Ecclesiastic
-
Ecclesiastic
-
Computer
Bayesian Filtering Library.
A Ph D in Bayesian Statistics.
Bayesian methods are characterized by concepts and procedures as follows.
So we would use Bayesian analysis to.
Bayesian statistics and the Chapman-Kolmogorov equation tell me that.
Now a key part to the Bayesian is this part of the formula.
Their programs generate pixel interpolation based on Bayesian analysis.
This is the simplest Bayesian derivation of the Doomsday Argument.
Pearl's breakthrough had been to use what were called Bayesian Belief Networks.
Understanding how the bayesian filtering works in SciKit and improving accuracy.
Different methodologies andtechniques may be employed to interpret emotion such as Bayesian networks.
Marginalization Paradoxes in Bayesian and Structural Inference.
Bayesian model comparison is a method of model selection based on Bayes factors.
His work in probability is developed along Bayesian lines and again aimed at application in the physical sciences.
Bayesian updating is particularly important in the dynamic analysis of a sequence of data.
The W{\displaystyle W\} in this formula is equivalent to a Bayesian posterior mean(see Bayesian statistics).
Bayesian statistics were popularized in the 1960s by Howard Raiffa for usage in business environments.
The additional hypotheses sufficient to(uniquely) specify Bayesian updating are substantial and not universally seen as satisfactory.
The third day focused on the presentation andassessment of new methodology for projecting fertility based on a Bayesian approach.
Decision trees Random forests Bayesian networks Support vector machines Neural networks Logistic regression Probit model.
To allow for a complete data set,such advanced estimation techniques as maximum entropy and Bayesian posterior density estimators are used.
And the key idea to Bayesian inference is you have two sources of information from which to make your inference.
I am able to successfully improve the performance of my XGBoost model through Bayesian optimization, but the best I can achieve through Bayesian.
A Bayesian hierarchical model was used combined with country-specific time trends, and the model accounted for differences by data source and sample population.
The Population Division cooperated with researchers from the University of Washington andthe University of Singapore to develop the Bayesian hierarchical model that was used in the probabilistic fertility projections.
Furthermore, in a Bayesian framework, combining forecasting techniques is the most reliable means of producing density forecasts.
The Division also continued collaborative work with the University of Washington and the University of Singapore on improving the methodology for thepreparation of probabilistic population projections based on a Bayesian approach.
According to Bayesian theory, managers make decisions, and managers should make decisions, based on a calculation of the probabilities of all the possible outcomes of a situation.
The Population Division cooperated with researchers from the University of Washington andthe University of Singapore to develop the Bayesian hierarchical model that was used in the probabilistic mortality and fertility projections.
And the point about Bayesian decision theory is it gives you the mathematics of the optimal way to combine your prior knowledge with your sensory evidence to generate new beliefs.