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Ensemble modeling
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Part 2 of ebook "The elements of statistical learning: Data mining, inference, and prediction (Second edition)" provides readers with contents including: Chapter 10 - Boosting and additive trees; Chapter 11 - Neural networks; Chapter 12 - Support vector machines and flexible discriminants; Chapter 13 - Prototype methods and nearest-neighbors; Chapter 14 - Unsupervised learning; Chapter 15 - Random forests; Chapter 16 - Ensemble learning; Chapter 17 - Undirected graphical models; Chapter 18 - High-dimensional problems p ≫ N;...
409p
daonhiennhien
03-07-2024
4
1
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Groundwater potential zoning using Logistics Model Trees based novel ensemble machine learning model
n this work, the main aim is to map the potential zones of groundwater in Central Highlands (Vietnam) using a novel ensemble machine learning model, namely CG-LMT, which is a combination of two advanced techniques, namely Cascade Generalization (CG) and Logistics Model Trees (LMT). For this, a total of 501 wells data and a set of twelve affecting factors were gathered and selected to generate training and testing datasets used for building and validating the model.
10p
dianmotminh02
03-05-2024
9
2
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A damage diagnosis method for trusses based on incomplete free vibration properties utilizing ensemble learning, e.g. Extreme gradient boosting (XGBoost), is presented in this work. Owing to the lack of measurement sensors, modal features are only measured at master degrees of freedom (DOFs) of a few first models instead of all DOFs of a structural system.
12p
viohoyo
25-04-2024
3
2
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Multi-omics data are good resources for prognosis and survival prediction; however, these are difficult to integrate computationally. We introduce DeepProg, a novel ensemble framework of deep-learning and machine-learning approaches that robustly predicts patient survival subtypes using multi-omics data.
15p
vibransone
28-03-2024
6
2
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In this study, a logistic regression model is developed to forecast tropical storm (TS) genesis in the Vietnam East Sea from 2012 to 2019. The model incorporates seven potential predictors including dynamic and thermodynamic parameters at formation time retrieved from the WRF-LETKF outputs.
12p
viellison
28-03-2024
3
1
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Ebook "Visualization of hydrogen-bond dynamics: Water-based model systems on a Cu(110) surface" have been carried out by means of spectroscopic methods where the signal stems from the ensemble of a system and the hydrogen-bond dynamics were inferred indirectly. This book addresses the direct imaging of hydrogen-bond dynamics within water-based model systems assembled on a metal surface, using a scanning tunneling microscope (STM).
139p
coduathanh1122
27-03-2024
2
1
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Part 2 book "An introduction to statistical mechanics and thermodynamics" includes content: Ensembles in classical statistical mechanics; classical ensembles - grand and otherwise; irreversibility; quantum ensembles; quantum canonical ensemble; black body radiation; the harmonic solid; ideal quantum gases; bose–einstein statistics; fermi–dirac statistics; insulators and semiconductors; phase transitions and the ising model;.... and other contents.
203p
muasambanhan06
01-02-2024
2
1
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This study proposes the application of Ensemble Decision Tree Boosted (EDT Boosted) model for forecasting the surface chloride concentration of marine concrete
13p
visharma
20-10-2023
6
4
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Bài viết Xây dựng mô hình máy học để dự báo lực bám dính giữa bê tông cốt thép và vật liệu FRP gia cường tập trung nghiên cứu vào xây dựng và so sánh các mô hình học máy khác nhau để dự báo lực bám dính giữa vật liệu bê tông cốt thép và vật liệu FRP gia cường. Các mô hình đơn (single model) và mô hình kết hợp (ensemble model) được sử dụng để giải quyết vấn đề này.
6p
visharma
20-10-2023
8
5
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Bài giảng Khai phá dữ liệu (Data mining): Ensemble models, chương này trình bày những nội dung về: introduction; voting; bagging; boosting; stacking and blending; learning ensembles; methods of constructing ensembles; bias-variance tradeoff; simple ensemble techniques;... Mời các bạn cùng tham khảo chi tiết nội dung bài giảng!
90p
diepkhinhchau
18-09-2023
5
5
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Accurate prediction models for spatial prediction of forest fire danger play a vital role in predicting forest fires, which can help prevent and mitigate the detrimental effects of such disasters. This research aims to develop a new ensemble learning model, HHO-RSCDT, capable of accurately predicting spatial patterns of forest fire danger.
19p
viisac
15-09-2023
3
3
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In this paper, we proposed two types of joint models for answerability prediction and pure-MRC prediction with/ without a dependency mechanism to learn the correlation between a start position and end position in pure-MRC output prediction.
7p
viberkshire
09-08-2023
6
3
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In this paper, we aim at proposing a Vietnamese ASR system for participating in the VLSP 2021 Automatic Speech Recognition Shared Task. The system is based on the Wav2vec 2.0 framework, along with the application of self-training and several data augmentation techniques.
7p
viberkshire
09-08-2023
9
4
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This study extends prior research by combining a chronological pharmacovigilance network approach with machine-learning (ML) techniques to predict adverse drug events (ADEs) based on the drugs’ similarities in terms of the proteins they target in the human body. The focus of this research, though, is particularly centered on predicting the drug-ADE associations for a set of 8 common and high-risk ADEs.
11p
visteverogers
24-06-2023
5
2
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The results show that the Belts–Millers–Janjic convection diagram and the WSM6 microphysics diagrams are suitable in the simulation of storm Damrey. Therefore, in this study, we apply multiphysics technique in combinatorial Kalman filter to determine the error of WRF model predicting the trajectory and intensity of storm Damrey 2017.
15p
viironman
02-06-2023
4
3
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To compare Cox models, machine learning (ML), and ensemble models combining both approaches, for prediction of stroke risk in a prospective study of Chinese adults. The results highlight the potential value of expanding the use of ML in clinical practice.
9p
vighostrider
25-05-2023
5
2
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This article describes an ensembling system to automatically extract adverse drug events and drug related entities from clinical narratives, which was developed for the 2018 n2c2 Shared Task Track 2. Materials and Methods: We designed a neural model to tackle both nested (entities embedded in other entities) and polysemous entities (entities annotated with multiple semantic types) based on MIMIC III discharge summaries.
9p
vighostrider
25-05-2023
3
2
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Ebook Machine learning algorithms: Part 2 presents the following content: Chapter 8: decision trees and ensemble learning, chapter 9: clustering fundamentals, chapter 10: hierarchical clustering, chapter 11: introduction to recommendation systems, chapter 12: introduction to natural language processing, chapter 13: topic modeling and sentiment analysis in NLP, chapter 14: a brief introduction to deep learning and tensorflow, chapter 15: creating a machine learning architecture.
184p
runthenight09
06-05-2023
8
4
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In Vietnam, the study of data assimilation has also been applied in the meteorology and has attracted the increasing interest in oceanography. This paper presents the results of the study to calculate the wave height data from satellites combined with measured wave height data at MSP1 station of Vietsovpetro using the Ensemble Kalman Filter (EnKF) method associated with SWAN wave model in the Eastern Vietnam Sea.
10p
vicaptainmarvel
21-04-2023
6
3
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To predict the characteristics of external causes of road trafc accident (RTA) injuries and mortality, we compared performances based on differences in the correction and classifcation techniques for imbalanced samples.
10p
viferrari
28-11-2022
3
2
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