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Political Media Discourse as an Interactional Space: Presidential TV Addresses to the Nation from a Metadiscourse Perspective [PDF]
Актуальные проблемы филологии и педагогической лингвистики, 2023 The study of political media discourse as an interactional space requires an analysis of not only its linguistic characteristics and propositional content but also its metadiscourse component, strategies employed to express speaker’s attitudes and ...
Olga А. Boginskaya
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Predicting the length of a post-accident absence in construction with boosted decision trees [PDF]
MATEC Web of Conferences, 2020 Work safety control and analysis of accidents during construction performance are one of the most important issues of construction management. The paper focuses on post-accident absence as an element of occupational safety management. Somehow, the length
Krawczyńska-Piechna Anna
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Spanish Journal of Agricultural Research, 2020 Aim of study: To predict genomic accuracy of binary traits considering different rates of disease incidence. Area of study: Simulation Material and methods: Two machine learning algorithms including Boosting and Random Forest (RF) as well as threshold ...
Yousef Naderi, Saadat Sadeghi
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MPSUBoost: A Modified Particle Stacking Undersampling Boosting Method
IEEE Access, 2022 Class imbalance problems are prevalent in the real world. In such cases, traditional supervised algorithms tend to have difficulty in recognizing minority data because the models are likely to maximize prediction accuracy by simply ignoring minority data.
Sang-Jin Kim, Dong-Joon Lim
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Cumhuriyet Science Journal, 2020 The purpose of this study is to classify the data set which is created by taking students who placed to universities from 81 provinces, in accordance with Undergraduate Placement Examination between the years 2010-2013 in Turkey, with Bagging and ...
Tuğba Tuğ Karoğlu, Hayrettin Okut
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Remote Sensing, 2021 In recent years, several powerful machine learning (ML) algorithms have been developed for image classification, especially those based on ensemble learning (EL).
Hamid Jafarzadeh +4 more
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Regression Models for Symbolic Interval-Valued Variables
Entropy, 2021 This paper presents new approaches to fit regression models for symbolic internal-valued variables, which are shown to improve and extend the center method suggested by Billard and Diday and the center and range method proposed by Lima-Neto, E.A.and De ...
Jose Emmanuel Chacón +1 more
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A comparative study of ensemble methods in the field of education: Bagging and Boosting algorithms
International Journal of Assessment Tools in Education, 2023 This study aims to conduct a comparative study of Bagging and Boosting algorithms among ensemble methods and to compare the classification performance of TreeNet and Random Forest methods using these algorithms on the data extracted from ABİDE ...
Hikmet Şevgin
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Boosting Additive Models using Component-wise P-Splines [PDF]
, 2007 We consider an efficient approximation of Bühlmann & Yu’s L2Boosting algorithm with component-wise smoothing splines. Smoothing spline base-learners are replaced by P-spline base-learners which yield similar prediction errors but are more advantageous ...
Hothorn, Torsten, Schmid, Matthias
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Algorithms, 2021 In machine learning, ensembles of models based on Multi-Layer Perceptrons (MLPs) or decision trees are considered successful models. However, explaining their responses is a complex problem that requires the creation of new methods of interpretation.
Guido Bologna
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