Advanced Machine Learning Ensembles for Improved Precipitation Forecasting: The Modified Stacking Ensemble Strategy in China by Tiantian Tang, Yifan Wu, Yujie Li, Lexi Xu, Xinyi Shi, Haitao Zhao, Guan Gui

Subjects: “…Ensemble methods…”
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Ensemble Classification Approach for Sarcasm Detection by Jyoti Godara, Isha Batra, Rajni Aron, Mohammad Shabaz

“…This research work introduces a scheme to detect sarcasm based on PCA algorithm, K-means algorithm, and ensemble classification. The four ensemble classifiers are designed with the objective of detecting the sarcasm. …”
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Nuclear Fusion Pattern Recognition by Ensemble Learning by G. Farias, E. Fabregas, I. Martínez, J. Vega, S. Dormido-Canto, H. Vargas

“…In the literature, several popular algorithms can be found to carry out the automatic classification of signals. Among these, ensemble methods provide a good balance between success rate and internal information about models. …”
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Global Optimization Ensemble Model for Classification Methods by Hina Anwar, Usman Qamar, Abdul Wahab Muzaffar Qureshi

“…This paper proposes a global optimization ensemble model for classification methods (GMC) that can improve the overall accuracy for supervised learning problems. …”
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Label iteration-based clustering ensemble algorithm by HE Yulin, YANG Jin, HUANG Zhexue, YIN Jianfei

Subjects: “…clustering ensemble algorithm…”
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<i>pathways-ensemble-analysis</i> v1.1.0: an open-source library for systematic and robust analysis of pathway ensembles by L. Welder, N. Grant, M. J. Gidden, M. J. Gidden

“…<p>Ensembles of mitigation pathways, produced by multiple different models, are becoming increasingly influential as the world seeks to define climate goals and implement policy to meet them. …”
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Synchronization in ensembles of coupled maps with a major element by Iryna Omelchenko, Yuri Maistrenko, Erik Mosekilde

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Ensemble graph auto-encoders for clustering and link prediction by Chengxin Xie, Jingui Huang, Yongjiang Shi, Hui Pang, Liting Gao, Xiumei Wen

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Modelling Laser Milling of Microcavities for the Manufacturing of DES with Ensembles by Pedro Santos, Daniel Teixidor, Jesus Maudes, Joaquim Ciurana

“…Ensemble regression emerged as the most suitable technique for studying this industrial problem. …”
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An Event Causality Identification Framework Using Ensemble Learning by Xiaoyang Wang, Wenjie Luo, Xiudan Yang

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Adaptive CNN Ensemble for Complex Multispectral Image Analysis by Syed Muslim Jameel, Manzoor Ahmed Hashmani, Mobashar Rehman, Arif Budiman

“…The adaptive CNN ensemble framework consists of five (05) modules, including dynamic ensemble classifier (DEC) module. …”
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In silico design of an epitope-based vaccine ensemble for fasliolopsiasis by Ruchishree Konhar, Ruchishree Konhar, Kanhu Charan Das, Kanhu Charan Das, Aiboklang Nongrum, Rohan Raj Samal, Shailesh Kumar Sarangi, Devendra Kumar Biswal, Devendra Kumar Biswal

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Statistical mechanics and machine learning of the α-Rényi ensemble by Andrew Jreissaty, Juan Carrasquilla

“…We study the statistical physics of the classical Ising model in the so-called α-Rényi ensemble, a finite-temperature thermal state approximation that minimizes a modified free energy based on the α-Rényi entropy. …”
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Driver Distraction Identification with an Ensemble of Convolutional Neural Networks by Hesham M. Eraqi, Yehya Abouelnaga, Mohamed H. Saad, Mohamed N. Moustafa

“…The system consists of a genetically weighted ensemble of convolutional neural networks; we show that a weighted ensemble of classifiers using a genetic algorithm yields a better classification confidence. …”
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Identification of maize kernel varieties based on interpretable ensemble algorithms by Chunguang Bi, Chunguang Bi, Xinhua Bi, Jinjing Liu, Hao Xie, Shuo Zhang, He Chen, Mohan Wang, Lei Shi, Lei Shi, Shaozhong Song

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An optimized ensemble grey wolf-based pipeline for monkeypox diagnosis by Ahmed I. Saleh, Asmaa H. Rabie, Shimaa E. ElSayyad, Ali E. Takieldeen, Fahmi Khalifa

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Severity Classification of Conjunctival Hyperaemia by Deep Neural Network Ensembles by Hiroki Masumoto, Hitoshi Tabuchi, Tsuyoshi Yoneda, Shunsuke Nakakura, Hideharu Ohsugi, Tamaki Sumi, Atsuki Fukushima

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Using Enstrophy-Based Diagnostics in an Ensemble for Two Blocking Events by Andrew D. Jensen, Anthony R. Lupo

“…In this paper, the enstrophy-based diagnostics are used to analyze two blocking events, using data from the ERA-Interim reanalysis data set (0.75° × 0.75°) and also the Global Ensemble Forecast System (GEFS) (1° × 1°). The results of this work indicate that using an ensemble may be more effective than a single dynamical control forecast in evaluating the enstrophy-based diagnostic quantities, and that the results are similar to those obtained with coarser resolution.…”
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Robust ensemble of handcrafted and learned approaches for DNA-binding proteins by Loris Nanni, Sheryl Brahnam

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An Approach for Demand Forecasting in Steel Industries Using Ensemble Learning by S. M. Taslim Uddin Raju, Amlan Sarker, Apurba Das, Md. Milon Islam, Mabrook S. Al-Rakhami, Atif M. Al-Amri, Tasniah Mohiuddin, Fahad R. Albogamy

“…This paper aims to introduce a robust framework for forecasting demand, including data preprocessing, data transformation and standardization, feature selection, cross-validation, and regression ensemble framework. Bagging (random forest regression (RFR)), boosting (gradient boosting regression (GBR) and extreme gradient boosting regression (XGBR)), and stacking (STACK) are employed as ensemble models. …”
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