[PDF] Top 20 Ensemble based Active Learning for Parse Selection
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Ensemble based Active Learning for Parse Selection
... Discriminant cost works as follows. Annotation for Redwoods does not consist of actually drawing parse trees, and instead involves picking the correct parse out those produced by the ERG. To facilitate this ... See full document
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<p>Machine Learning For Tuning, Selection, And Ensemble Of Multiple Risk Scores For Predicting Type 2 Diabetes</p>
... is classi fi ed in high-risk group, but only the males with BMI >30 kg/m 2 or WC >102 cm will be considered as high-risk for Western population. These deviations in per- formance are attributed to differences in ... See full document
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Structural Correspondence Learning for Parse Disambiguation
... pendency based) treebank grammars (Charniak, 1996). Parse selection constitutes an important part of many parsing systems (Johnson et ...of parse selection models to novel domains is a ... See full document
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A Comparison of Structural Correspondence Learning and Self training for Discriminative Parse Selection
... Correspondence Learning has been applied successfully to PoS tagging and Sen- timent Analysis (Blitzer et ...teams. Based on annotation differences in the datasets (Dredze et ...to parse disam- ... See full document
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Improving Classifier Performance Using Feature Selection with Ensemble Learning
... feature selection is selecting a subset of relevant features for generating strong learning ...feature selection with filling the missing values in order to improve the performance of the ... See full document
5
Learning Discourse Relations with Active Data Selection
... Since the committee- based sampling method was originally devel- oped for probabilistic classifiers, we extended the method for a decision tree classifier, us-.. ing a statistical techni[r] ... See full document
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Active learning query selection with historical information
... an active learning strategy is that the number of parameters that require tuning be minimal, since there are typically no validation ...parameters based on the current performance of active ... See full document
209
Predicting bruise susceptibility in apples using Vis/SWNIR technique combined with ensemble learning
... selective ensemble learning model based on feature selection (SELFS) to predict bruise susceptibility in ...feature selection method based on successful projection algorithm ... See full document
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An Ensemble of Classifiers using Weighted Instance Selection
... Computing based approaches, Support Vector based approaches. An Ensemble of Classifiers is another approach in data ...mining. Ensemble of Classifiers is powerful technique in classification ... See full document
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Semi-Supervised Clustering for High Dimensional Data Clustering
... are based on active learning, with ensemble clustering-means algorithm, data streams with flock, fuzzyclustering for shape annotations, Incremental semi supervised clustering, Weakly ... See full document
5
AdaBoost Ensemble Learning Technique for Optimal Feature Subset Selection
... BN learning can be categorized into two approaches that are parametric and structural ...Parametric learning is used for learning the parameters when the structure is ...Structural learning ... See full document
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Squibs: Automatic Selection of HPSG Parsed Sentences for Treebank Construction
... parser ensemble approach based on full agreement between a MaxEnt model and a dependency parser to select correct linguistic analyses output by an HPSG ...manual parse selection, which makes ... See full document
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An Integrated Approach to Robust Processing of Situated Spoken Dialogue
... the parse selection module. The parse selec- tion is based on a discriminative model exploring a set of relevant semantic, syntactic, contextual and acoustic features extracted for each ...The ... See full document
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Ensemble feature subset selection technique in spam detection system
... an ensemble feature selection technique as a supervised learning method by combining the filter-based and wrapper-based ...voting based on feature ...(2006) based on the ... See full document
6
Multi Task Active Learning for Linguistic Annotations
... single-task active learning (AL) approach. In the multi-task ac- tive learning (MTAL) paradigm, we select ex- amples for several annotation tasks rather than for a single one as usually done in the ... See full document
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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING
... the ensemble learning schemes can be utilized for software defect ...prediction. based on these assumptions, Tong et ...two-stage ensemble learning ...deep learning schemes where ... See full document
9
An ensemble based feature selection methodology for case based learning
... group learning, as well as in communication and critical thinking, to acquire meaningful knowledge for improving students’ attitudes towards medical education ... See full document
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Active learning for HPSG parse selection
... Active learning has been successfully applied to a number of natural language oriented tasks, including text categorization (Lewis and Gale, 1994) and part-of-speech tagging (Engelson and Dagan, ... See full document
8
A* Parsing: Fast Exact Viterbi Parse Selection
... While the A* estimates given here can be used to accel- erate PCFG parsing, most high-performance parsing has utilized models over lexicalized trees. These A* methods can be adapted to the lexicalized case. In Klein and ... See full document
8
Parsing of Partially Bracketed Structures for Parse Selection
... not. Parse selec- tion is not constrained to be unidirectional, and at each iteration, brackets can be placed at arbitrary positions in the input sentence, and thereupon the most likely parse is ... See full document
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