AMWSPLAdaboost Credit Card Fraud Detection Method Based on Enhanced Base Classifier Diversity by Wang Ning, Siliang Chen, Songyi Lei, Xiongbin Liao

“…Therefore, this paper uses an adaptive hybrid weighted self-paced learning method to improve the objective function of the Adaboost algorithm, thus changing the strategy of base learner selection in the Adaboost algorithm, while the self-paced learning selected in this paper The self-adaptive threshold finding algorithm selected in this paper can well mitigate the influence of human experience on model training. …”
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Adaptive data-driven selection of sequences of biological and cognitive markers in pre-clinical diagnosis of dementia by Patric Wyss, David Ginsbourger, Haochang Shou, Christos Davatzikos, Stefan Klöppel, Ahmed Abdulkadir

“…The sequential algorithm selected 14 percent of available measurements and concluded after an average follow-up time of 0.74 years at the expense of 0.05 lower accuracy. …”
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Selection of an Efficient Classification Algorithm for Ambient Assisted Living: Supportive Care for Elderly People by Reyadh Alluhaibi, Nawaf Alharbe, Abeer Aljohani, Rabia Emhmed Al Mamlook

“…With the development of numerous classification algorithms, selecting the best classifier became a vital and challenging step in technology acceptance. …”
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Efficient Exploitation of Radio Frequency and Visible Light Communication Bands for D2D in Mobile Networks by Mehyar Najla, Pavel Mach, Zdenek Becvar, Petr Chvojka, Stanislav Zvanovec

“…To solve this problem, we design a centralized low-complexity heuristic algorithm selecting either RF or VLC band for each D2D pair relying on the mutual interference among the pairs. …”
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PREDICTING THE RISK OF PROTHROMBOTIC CHANGES IN ADOLESCENTS WITH ESSENTIAL HYPERTENSION by S. E. Bolshakova, M. V. Gomellya, T. A. Bairova, O. N. Berdina, O. V. Bugun, I. M. Mikhalevich, L. V. Rychkova

“…To create a mathematical model of forecasting, discriminant analysis was used, with the help of which from the 59 proposed predictors the algorithm selected 8 most informative features: the C777T polymorphism of the 5,10-methylenetetrahydrofolate reductase gene, the A66G gene of the methionine synthase reductase gene, the daily diastolic blood pressure level, the level of the nocturnal systolic arterial pressure-time index of hypertension, systolic blood pressure during the day, weighed down by thrombotic genealogically history, early onset of thrombosis, burdened thrombotic genealogical history. …”
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LHCb Topological Trigger Reoptimization by Likhomanenko, Tatiana, Khairullin, Egor, Rogozhnikov, Alex, Ustyuzhanin, Andrey, Ilten, Philip J, Williams, Michael

“…In the LHC Run 1, this trigger, which utilized a custom boosted decision tree algorithm, selected a nearly 100% pure sample of b-hadrons with a typical efficiency of 60-70%; its output was used in about 60% of LHCb papers. …”
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Resilient Monotone Sequential Maximization by Tzoumas, V, Jadbabaie, A, Pappas, GJ

“…In this paper, we provide the first scalable algorithm, that achieves the following characteristics: system-wide resiliency, i.e., the algorithm is valid for any number of denial-of-service attacks, deletions, or failures; adaptiveness, i.e., at each time step, the algorithm selects system elements based on the history of inflicted attacks, deletions, or failures; and provable approximation performance, i.e., the algorithm guarantees for monotone objective functions a solution close to the optimal. …”
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A particle swarm optimization and min-max­-based workflow scheduling algorithm with QoS satisfaction for service-­oriented grids by Ambursa, Faruku Umar, Latip, Rohaya, Abdullah, Azizol, K. Subramaniam, Shamala

“…In this paper, a constraints-aware multi-QoS workflow scheduling strategy is proposed based on particle swarm optimization (PSO) and a proposed look-ahead heuristic (LAPSO) to improve performance in such situations. The algorithm selects the best scheduling solutions based on the proposed constraint-handling strategy. …”
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A vaccine encoding conserved promiscuous HIV CD4 epitopes induces broad T cell responses in mice transgenic to multiple common HLA class II molecules. by Susan Pereira Ribeiro, Daniela Santoro Rosa, Simone Gonçalves Fonseca, Eliane Conti Mairena, Edilberto Postól, Sergio Costa Oliveira, Luiza Guilherme, Jorge Kalil, Edecio Cunha-Neto

“…Using rational vaccine design, we developed a DNA vaccine encoding 18 algorithm-selected conserved, "promiscuous" (multiple HLA-DR-binding) B-subtype HIV CD4 epitopes - previously found to be frequently recognized by HIV-infected patients. …”
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A machine learning-based treatment prediction model using whole genome variants of hepatitis C virus. by Hiroaki Haga, Hidenori Sato, Ayumi Koseki, Takafumi Saito, Kazuo Okumoto, Kyoko Hoshikawa, Tomohiro Katsumi, Kei Mizuno, Taketo Nishina, Yoshiyuki Ueno

“…The training data set was subject to nine machine-learning algorithms selected to identify the optimized combination of functional variants in relation to SVR status following DAA therapy. …”
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Local Random Walk Based Label Propagation Algorithm by LIU Yang, ZHENG Wen-ping, ZHANG Chuan, WANG Wen-jian

“…Community structure is one of the important characteristics of complex networks.Identifying communities of different functions in a network plays an important role for revealing important characteristics of complex networks.The community discovery algorithm based on label propagation uses the community label of direct neighbors of a node to updates its label,which might obtain inaccurate community structures.Furthermore,the results of multiple runs of the algorithm might be unstable.To solve this problem,a local random walk based label propagation algorithm(LRW-LPA) is proposed.First,the local importance of each node in its <i>k</i>-step neighborhood is calculated.Then,the node with the lowest local importance is selected as the starting node to perform the local random walk process.When walking out of the specified neighborhood,the random walker will return to the starting node and start the random walk again.Finally,the algorithm selects the label with the most occurrences in the local neighborhood to update the label of the starting node,and selects the label of the node with highest importance when there are multiple labels with the most occurrences.Due to LRW-LPA can determine an appropriate neighborhood of a node by adopting the local random walk process with restart,the stability of the algorithm improves greatly.Compared with LPA,BGLL,Infomap,Leiden,Walktrap and other classical algorithms on 12 real networks and 12 synthetic networks,it shows that the proposed LRW-LPA algorithm performs well in terms of normal mutual index(NMI),adjusted rand index(ARI) and modularity(Q).…”
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Feature Selection Using Neighborhood based Entropy by Fatemeh Farnaghi-Zadeh, Mohsen Rahmani, Maryam Amiri

“…In the next step, the significance of each feature is computed and a greedy algorithm selects appropriate features. The performance of the proposed approach is compared to both the commonest and newest methods of feature selection. …”
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Primitive fitting based on the efficient multiBaySAC algorithm. by Zhizhong Kang, Zhen Li

“…Although RANSAC is proven to be robust, the original RANSAC algorithm selects hypothesis sets at random, generating numerous iterations and high computational costs because many hypothesis sets are contaminated with outliers. …”
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Data Distribution Optimization Strategy in Wireless Sensor Networks With Edge Computing by Guozhi Li, Xuekun Song

“…The effective transmission network construction (ETNC) algorithm selects the available transmission links based on the set of available nodes. …”
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Systematic Literature Review and Benchmarking for Photovoltaic MPPT Techniques by Hsen Abidi, Lilia Sidhom, Ines Chihi

“…The mode of implementation (digital or analog), design simplicity, sensor requirements, convergence speed, range of efficacy, and hardware costs are the primary distinctions between these algorithms. Selecting an appropriate algorithm is critical for users, as it influences the electrical efficiency of PV systems and lowers costs by reducing the number of solar panels required to achieve the desired output. …”
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Hybrid Strategy of Bioinformatics Modeling (in silico): Biologically Active Peptides of Milk Protein by Alexandr G. Kruchinin, Ekaterina I. Bolshakova

“…The strategy algorithm relies on analytical data on the protein profile, the amino acid sequence of proteins that make up the raw material, taking into account their polymorphism, and the subsequent identification of bioactive amino acid sites in the protein structure. The algorithm selects optimal enzyme preparations, as well as models the hydrolysis and assesses the peptide bioactivity using proteomic databases. …”
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Pattern Recognition of Food Security in Indonesia Using Biclustering Plaid Model by Nur Hikmah, I Made Sumertajaya, Farit Mochamad Afendi

“…Biclustering come in various algorithms, selecting the most suitable biclustering algorithm can be a challenging task. …”
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Pilot design for underwater MIMO cosparse channel estimation based on compressed sensing by Yun Li, Lingxia Liao, Shanlin Sun, Zhicheng Tan, Xing Yao

“…When replacing each pilot indices position, the algorithm selects multiple pilot indices with the least cross-correlation from the alternative positions to replace the current pilot indices position, and it uses the inner and outer two-layer loops to realize the bit-by-bit optimal replacement of the pilot. …”
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Video adaptive watermark embedding and detection algorithm based on phase function equation by Chao Yan, Wang Hao, Liu Shuying, Shorman Samer

“…When the coding rate is 2.6Mvps, the accuracy of each plane is 100%, 96.38%, 94.87% and 95.21% respectively. This algorithm selects the frame of video to embed watermark. …”
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sCwc/sLcc: Highly Scalable Feature Selection Algorithms by Kilho Shin, Tetsuji Kuboyama, Takako Hashimoto, Dave Shepard

“…In addition, we introduce a fast implementation of our algorithms: sCwc does not require any adjusting parameter, while sLcc requires a threshold parameter, which we can use to control the number of features that the algorithm selects.…”
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