Combining Models that Utilise Different Features
Combining Knowledge from Different Sources in Causal Probabilistic Models
... probabilistic models usually combine various sources of infor- mation, such as existing textbooks, statistical reports, databases, and expert ...that different population characteristics, such as sex, race, ...
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Combining Different Features of Idiomaticity for the Automatic Classification of Noun+Verb Expressions in Basque
... of different features of idiomaticity in the characterization of NV expressions, and the results obtained combining them using ML ...other features contribute to improve the results, ...
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Weasel: a machine learning based approach to entity linking combining different features
... different features that is trained using a Support Vector ...four features that quantify i) the likelihood that the actual name refers to the resource candidate (extracted from Wikipedia anchors), ii) the ...
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An evaluation of different features and learning models for anomalous event detection
... location features results are poor, but once the optical flow features are per- spective normalized, results significantly improve with all the ...the different feature com- binations with ...
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Improving accuracy of downscaling rainfall by combining predictions of different statistical downscale models
... primary models have been compared with two combining models in terms of their ability to downscale daily rainfall over a selected site in Northwest ...and combining model to downscale the ...
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Improving accuracy of downscaling rainfall by combining predictions of different statistical downscale models
... these models were used as inputs to Artificial Neural Network ...(SAM), combining models (SDSM, Multiple linear regressions (MLR), Generalized Linear Model (GLM)) were applied to a studied site in ...
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Improving accuracy of downscaling rainfall by combining predictions of different statistical downscale models
... primary models have been compared with two combining models in terms of their ability to downscale daily rainfall over a selected site in Northwest ...and combining model to downscale the ...
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Using different classification models in wheat grading utilizing visual features
... sification models (Luo et ...logical features, texture and wavelet features and their ...wavelet features along with a linear discriminant classifi- er were recognized as the best ...
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Combining electronic and structural features in machine learning models to predict organic solar cells properties
... descriptors related to different physical phenomena was included. Each additional descriptor increases the computational cost related to obtaining the input, with the additional downside of missing elements ...
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Combining Textual and Graph-based Features for Named Entity Disambiguation Using Undirected Probabilistic Graphical Models
... text-based features, namely i) term frequency scores, ii) a similarity measure based on the Levenshtein distance and iii) the document ...includes features measuring the degree of connect- edness between ...
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Combining Contextual Features for Word Sense Disambiguation
... ing different subsets of possible ...with different combinations of lo- cal/topical features, we attempted to undo passiviza- tion transformations to recover underlying subjects and ...
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Combining Contextual Features for Word Sense Disambiguation
... ing different subsets of possible ...with different combinations of lo- cal/topical features, we attempted to undo passiviza- tion transformations to recover underlying subjects and ...
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A general framework for combining ecosystem models
... under different management ...by combining their prior beliefs with information from data and model- ...allowing different individuals’ posterior distributions to be ...
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Combining Linguistic Features for the Detection of Croatian Multiword Expressions
... All models were trained and tested using 10-fold cross-validation on the gold ...line models was optimized on the train ...considered models in terms of both accuracy and F1-score by a consid- erable ...
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A Framework for Combining Acoustic and Textual Features in Sentiment Analysis
... three different feature sets are investigated by using well performing ...emotion features can be combined with lexicon based sentiment features in machine learning based sentiment analysis ...
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Salient Object Detection via Combining Duplex Features
... N c is the maximum color distance, which is generally taken as 10; N s is the maximum distance between seeds, and is set to N s S . The SLIC algorithm can effectively segment the image into super-pixel blocks with ...
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NTNU CORE: Combining strong features for semantic similarity
... Reused Features The TakeLab ‘simple’ system ( ˇSari´c et ...its features, that is, n-gram overlap, WordNet-augmented word overlap, vector space sentence similarity, normalized differ- ence, shallow NE ...
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Combining Features and Semantics for Low-level Computer Vision
... In this section, we summarize our approach and our findings for each proposed solu- tion in the thesis. We emphasize the advantages of using high-level cues for matching- based problems and point out remaining challenges ...
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Semantic Medical Image Analysis For Combining Visual Features
... In particular fields, in particular in the therapeutic area, outright shading or dark level components are regularly of extremely restricted expressive power unless correct reference focuses exist as it is the situation ...
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Using holistic features for scene classification by combining classifiers
... The scene classification is an important topic in computer vision. However, while classifying a scene is not a problem for humans, it is quite a challenging task for computers. Among the reasons is the significant ...
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