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Knowledge of the conditional is conditional knowledge (that is, conditional upon learning the antecedent and applying the inference rule modus ponens: If P then Q, P, therefore Q).
The compensation rules of a wide range of model adaptation, missing feature, and uncertainty decoding approaches can be expressed by modifying the Bayesian network structure of a conventional HMM and applying the inference rules of Bayesian networks [26] potentially followed by suitable approximations to ensure mathematical tractability.
By applying the inference rules in the reverse order and by reiterating this inverse process, it will be possible to logically reconstruct several possible paths that lead to B. The initial node in each reconstructed path will be an aggregate from which the conclusion could be obtained, even though this might not match the experimental initial aggregate.
The aim of applying the inference approach to such synthetic networks is to investigate the quality of the inference in a case where the underlying network is known.
This means, instead of applying the inference method to one data set, we are applying it to a bootstrap [ 22] ensemble of data sets.
Using our software as a inference method, independently of prior biological information, we input information about the network topology obtained by first applying the inference method from Jarrah et al. in [ 19] to the available data with the added noise.
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Then, different algorithms to implement a given inference system should be specified as strategies to apply the inference rules.
Similarly, Della Gatta et al. [ 41] applied the inference method ARACNE to reverse-engineer a genome-scale GRN in leukemia.
I applied the inference procedure to Clone H and found that the VH gene segments with the greatest posterior probabilities are VH4-34*01 and VH4-34*03, with nearly identical posterior probabilities of 0.49 each.
In our experiments, we applied the inference process described previously to all TREATS relationships in SemMedDB involving represented neoplastic processes (UMLS semantic type neop) unrelated to prostate cancer, and retrieved the most strongly associated reasoning path in each case.
Applying the variational inference algorithm to StructHDP would improve its speed significantly.
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