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probabilistic    
概率性的; 随机; 不确定性的

概率性的; 随机; 不确定性的

probabilistic
adj 1: of or relating to the Roman Catholic philosophy of
probabilism
2: of or relating to or based on probability; "probabilistic
quantum theory"


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  • Is there any difference between Random and Probabilistic?
    It seems i can't directly say probabilistic and random are identical But this is telling : random experiment is a probabilistic experiment Is there any difference between Random and Probabili
  • What is the importance of probabilistic machine learning?
    Contemporary machine learning, as a field, requires more familiarity with Bayesian methods and with probabilistic mathematics than does traditional statistics or even the quantitative social sciences, where frequentist statistical methods still dominate Those coming from Physics are less likely to be surprised by the importance of probabilities in ML since quantum physics is so thoroughly
  • Whats the difference between probability and statistics?
    The short answer to this I've heard from Persi Diaconis is the following: The problems considered by probability and statistics are inverse to each other In probability theory we consider some underlying process which has some randomness or uncertainty modeled by random variables, and we figure out what happens In statistics we observe something that has happened, and try to figure out what
  • What is probabilistic inference? - Cross Validated
    Is probabilistic inference only applicable in a graphical modelling context? What's the distinction between traditional statistical inference (p-values, confidence intervals, Bayes factors etc ) and probabilistic inference?
  • Probability model vs statistical model vs stochastic model
    The term ' Probability Model ' (probabilistic model) is usually an alias for stochastic model References: 1 Using statistical methods to model the fine-tuning of molecular machines and systems Steinar Thorvaldsen, Ola Hossjer [2] Statistics (Point Estimation) - Lecture One Charlotte Wickham - Berkeley
  • Probabilistic vs. other approaches to machine learning
    On the other hand, from statistical points (probabilistic approach) of view, we may emphasize more on generative models For example, mixture of Gaussian Model, Bayesian Network, etc The book by Murphy "machine learning a probabilistic perspective" may give you a better idea on this branch
  • How to derive the probabilistic interpretation of the AUC?
    The situation with the probabilistic interpretation is about A randomly chosen "positive" one (from the original positive class) A randomly chosen "negative" one (from the original negative class) Here is an answer that gives some graphical intuïtion I generated some data from which to calculate the ROC curve positives: 981 912 839 804 766
  • What is the difference between regular PCA and probabilistic PCA . . .
    I know regular PCA does not follow probabilistic model for observed data So what is the basic difference between PCA and PPCA? In PPCA latent variable model contains for example observed variable
  • How is the VAE encoder and decoder probabilistic?
    I think your view is correct, indeed the probabilistic nature of VAEs stems from parametrizing the latent distribution and then sampling from it I would argue that this procedure influences the whole network, making them more capable of generalization but also more prone to noisy reconstruction (often seen in GANs vs VAE comparisons) Of course, this doesn't make the rest of the network
  • What is the difference between the probabilistic and non-probabilistic . . .
    A probabilistic approach (such as Random Forest) would yield a probability distribution over a set of classes for each input sample A deterministic approach (such as SVM) does not model the distribution of classes but rather separates the feature space and return the class associated with the space where a sample originates from





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