Bayesian tree models
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This book "Data mining: Concepts and Techniques (Third edition)" is an extensive and detailed guide to the principal ideas, techniques and technologies of data mining. The book is organised in 13 substantial chapters, each of which is essentially standalone, but with useful references to the book’s coverage of underlying concepts. Please refer to the content of part 2 of book.
377p britaikridanik 05-07-2022 18 5 Download
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Although tuberculosis accounts for the highest mortality from a bacterial infection on a global scale, questions persist regarding its origin. One hypothesis based on modern Mycobacterium tuberculosis complex (MTBC) genomes suggests their most recent common ancestor followed human migrations out of Africa approximately 70,000 years before present.
24p viarchimedes 26-01-2022 10 0 Download
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The incidence and adverse events of postoperative blood transfusion in spinal tuberculosis (TB) have attracted increasing attention. Our purpose was to develop a prediction model to evaluate blood transfusion risk after spinal fusion (SF) for spinal TB.
11p vimackenziebezos 30-11-2021 10 2 Download
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Cancer progression is caused by the sequential accumulation of mutations, but not all orders of accumulation are equally likely. When the fixation of some mutations depends on the presence of previous ones, identifying restrictions in the order of accumulation of mutations can lead to the discovery of therapeutic targets and diagnostic markers.
26p vikentucky2711 26-11-2020 10 1 Download
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Branch-length parameters are a central component of phylogenetic models and of intrinsic biological interest. Default branch-length priors in some Bayesian phylogenetic software can be unintentionally informative and lead to branch- and tree-length estimates that are unreasonable.
6p vioklahoma2711 19-11-2020 8 1 Download
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Genome-wide association studies (GWASs) have been widely used to discover the genetic basis of complex phenotypes. However, standard single-SNP GWASs suffer from lack of power. In particular, they do not directly account for linkage disequilibrium, that is the dependences between SNPs (Single Nucleotide Polymorphisms).
24p viconnecticut2711 28-10-2020 10 1 Download
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Understanding the relation between the human microbiome and modulating factors, such as diet, may help researchers design intervention strategies that promote and maintain healthy microbial communities. Numerous analytical tools are available to help identify these relations, oftentimes via automated variable selection methods.
10p vicolorado2711 22-10-2020 14 0 Download
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This paper presents an approach of achieving adaptive e-learning by probabilistically evaluating a learner based not only on the profile and performance data of the learner but also on the data of previous learners. In this approach, an adaptation rule specification language and a user interface tool are provided to a content author or instructor to define adaptation rules. The defined rules are activated at different stages of processing the learning activities of an activity tree which models a composite learning object.
20p quenchua1 06-11-2019 18 1 Download
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We investigate the task of unsupervised constituency parsing from bilingual parallel corpora. Our goal is to use bilingual cues to learn improved parsing models for each language and to evaluate these models on held-out monolingual test data. We formulate a generative Bayesian model which seeks to explain the observed parallel data through a combination of bilingual and monolingual parameters. To this end, we adapt a formalism known as unordered tree alignment to our probabilistic setting.
9p hongphan_1 14-04-2013 46 3 Download
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We propose a model that incorporates an insertion operator in Bayesian tree substitution grammars (BTSG). Tree insertion is helpful for modeling syntax patterns accurately with fewer grammar rules than BTSG. The experimental parsing results show that our model outperforms a standard PCFG and BTSG for a small dataset. For a large dataset, our model obtains comparable results to BTSG, making the number of grammar rules much smaller than with BTSG.
6p hongdo_1 12-04-2013 34 3 Download
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We propose a non-parametric Bayesian model for unsupervised semantic parsing. Following Poon and Domingos (2009), we consider a semantic parsing setting where the goal is to (1) decompose the syntactic dependency tree of a sentence into fragments, (2) assign each of these fragments to a cluster of semantically equivalent syntactic structures, and (3) predict predicate-argument relations between the fragments.
11p hongdo_1 12-04-2013 46 3 Download
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Learning a tree substitution grammar is very challenging due to derivational ambiguity. Our recent approach used a Bayesian non-parametric model to induce good derivations from treebanked input (Cohn et al., 2009), biasing towards small grammars composed of small generalisable productions. In this paper we present a novel training method for the model using a blocked Metropolis-Hastings sampler in place of the previous method’s local Gibbs sampler.
6p hongdo_1 12-04-2013 47 2 Download
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This paper establishes a connection between two apparently very different kinds of probabilistic models. Latent Dirichlet Allocation (LDA) models are used as “topic models” to produce a lowdimensional representation of documents, while Probabilistic Context-Free Grammars (PCFGs) define distributions over trees. The paper begins by showing that LDA topic models can be viewed as a special kind of PCFG, so Bayesian inference for PCFGs can be used to infer Topic Models as well. Adaptor Grammars (AGs) are a hierarchical, non-parameteric Bayesian extension of PCFGs. ...
10p hongdo_1 12-04-2013 58 2 Download
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We present a Bayesian nonparametric model for estimating tree insertion grammars (TIG), building upon recent work in Bayesian inference of tree substitution grammars (TSG) via Dirichlet processes. Under our general variant of TIG, grammars are estimated via the Metropolis-Hastings algorithm that uses a context free grammar transformation as a proposal, which allows for cubic-time string parsing as well as tree-wide joint sampling of derivations in the spirit of Cohn and Blunsom (2010).
5p nghetay_1 07-04-2013 36 3 Download
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Many semantic parsing models use tree transformations to map between natural language and meaning representation. However, while tree transformations are central to several state-of-the-art approaches, little use has been made of the rich literature on tree automata. This paper makes the connection concrete with a tree transducer based semantic parsing model and suggests that other models can be interpreted in a similar framework, increasing the generality of their contributions.
9p nghetay_1 07-04-2013 39 1 Download
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We propose Symbol-Refined Tree Substitution Grammars (SR-TSGs) for syntactic parsing. An SR-TSG is an extension of the conventional TSG model where each nonterminal symbol can be refined (subcategorized) to fit the training data. We aim to provide a unified model where TSG rules and symbol refinement are learned from training data in a fully automatic and consistent fashion.
9p nghetay_1 07-04-2013 33 2 Download
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Tham khảo sách 'probabilistic modeling in bioinformatics and medical informatics', y tế - sức khoẻ, y học thường thức phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả
510p hyperion75 22-01-2013 51 4 Download