Search Results - "CLASSIFICATION algorithms"

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security by Al-Garadi, Mohammed Ali, Mohamed, Amr, Al-Ali, Abdulla Khalid, Du, Xiaojiang, Ali, Ihsan, Guizani, Mohsen

“…The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. IoT is one of the…”
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Recent advances in decision trees: an updated survey by Costa, Vinícius G., Pedreira, Carlos E.

“…Decision Trees (DTs) are predictive models in supervised learning, known not only for their unquestionable utility in a wide range of applications but also for…”
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A Survey on Multi-Task Learning by Zhang, Yu, Yang, Qiang

“…Multi-Task Learning (MTL) is a learning paradigm in machine learning and its aim is to leverage useful information contained in multiple related tasks to help…”
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The Wasserstein-Fourier Distance for Stationary Time Series by Cazelles, Elsa, Robert, Arnaud, Tobar, Felipe

“…We propose the Wasserstein-Fourier (WF) distance to measure the (dis)similarity between time series by quantifying the displacement of their energy across…”
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Corrections to "Contrastive Graph Pooling for Explainable Classification of Brain Networks" by Xu, Jiaxing, Bian, Qingtian, Li, Xinhang, Zhang, Aihu, Ke, Yiping, Qiao, Miao, Zhang, Wei, Khang Jeremy Sim, Wei, Gulyas, Balazs

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Bearing Fault Detection by a Novel Condition-Monitoring Scheme Based on Statistical-Time Features and Neural Networks by Prieto, M. D., Cirrincione, G., Espinosa, A. G., Ortega, J. A., Henao, H.

“…Bearing degradation is the most common source of faults in electrical machines. In this context, this work presents a novel monitoring scheme applied to…”
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A Comparative Study of Classification Algorithms for Early Detection of Diabetes by Carpinteiro, César, Lopes, João, Abelha, António, Santos, Manuel Filipe

“…Diabetes is a chronic disease that affects millions of people worldwide. Early detection of diabetes is crucial for preventing or delaying the onset of its…”
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Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery by Thanh Noi, Phan, Kappas, Martin

“…In previous classification studies, three non-parametric classifiers, Random Forest (RF), k-Nearest Neighbor (kNN), and Support Vector Machine (SVM), were…”
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Graph-in-Graph Convolutional Network for Hyperspectral Image Classification by Jia, Sen, Jiang, Shuguo, Zhang, Shuyu, Xu, Meng, Jia, Xiuping

“…With the development of hyperspectral sensors, accessible hyperspectral images (HSIs) are increasing, and pixel-oriented classification has attracted much…”
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Multimodal Multiobjective Evolutionary Optimization With Dual Clustering in Decision and Objective Spaces by Lin, Qiuzhen, Lin, Wu, Zhu, Zexuan, Gong, Maoguo, Li, Jianqiang, Coello, Carlos A. Coello

“…This article suggests a multimodal multiobjective evolutionary algorithm with dual clustering in decision and objective spaces. One clustering is run in…”
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Assessing implicit computational thinking in Zoombinis puzzle gameplay by Rowe, Elizabeth, Almeda, Ma Victoria, Asbell-Clarke, Jodi, Scruggs, Richard, Baker, Ryan, Bardar, Erin, Gasca, Santiago

“…There has been growing interest in assessing computational thinking (CT) across diverse learners beyond the traditional forms of tests and assignments…”
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Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning by Chen, Yinbo, Liu, Zhuang, Xu, Huijuan, Darrell, Trevor, Wang, Xiaolong

“…Meta-learning has been the most common framework for few-shot learning in recent years. It learns the model from collections of few-shot classification tasks,…”
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Machine learning based phishing detection from URLs by Sahingoz, Ozgur Koray, Buber, Ebubekir, Demir, Onder, Diri, Banu

“…•Use of 7 different classification algorithms and NLP based features.•A Big URL Data Set is produced and shared (36,400 legitimate and 37,175…”
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Influence Maximization on Social Graphs: A Survey by Li, Yuchen, Fan, Ju, Wang, Yanhao, Tan, Kian-Lee

“…Influence Maximization (IM), which selects a set of k users (called seed set) from a social network to maximize the expected number of influenced users (called…”
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Reliable Accuracy Estimates from k-Fold Cross Validation by Wong, Tzu-Tsung, Yeh, Po-Yang

“…It is popular to evaluate the performance of classification algorithms by k -fold cross validation. A reliable accuracy estimate will have a relatively small…”
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Hyperspectral Band Selection: A Review by Sun, Weiwei, Du, Qian

“…A hyperspectral imaging sensor collects detailed spectral responses from ground objects using hundreds of narrow bands; this technology is used in many…”
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A Survey of Ensemble Learning: Concepts, Algorithms, Applications, and Prospects by Mienye, Ibomoiye Domor, Sun, Yanxia

“…Ensemble learning techniques have achieved state-of-the-art performance in diverse machine learning applications by combining the predictions from two or more…”
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A Novel Method for Imbalanced Fault Diagnosis of Rotating Machinery Based on Generative Adversarial Networks by Li, Zhenxiang, Zheng, Taisheng, Wang, Yang, Cao, Zhi, Guo, Zhiqi, Fu, Hongyong

“…In the real scenario of engineering, the failure time of rotating machinery is generally much less than when it is in a healthy condition. Considering the…”
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A Novel Deep Ensemble Method for Selective Classification of Electrocardiograms by Argha, Ahmadreza, Alinejad-Rokny, Hamid, Baumgartner, Martin, Schreier, Gunter, Celler, Branko G., Redmond, Stephen J., Butcher, Ken, Ooi, Sze-Yuan, Lovell, Nigel H.

“…Objective: Telehealth paradigms are essential for remotely managing patients with chronic conditions. To assist clinicians in handling the large volumes of…”
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Correlation-Guided Updating Strategy for Feature Selection in Classification With Surrogate-Assisted Particle Swarm Optimization by Chen, Ke, Xue, Bing, Zhang, Mengjie, Zhou, Fengyu

“…Classification data are usually represented by many features, but not all of them are useful. Without domain knowledge, it is challenging to determine which…”
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