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Variable Selection in Data Analysis: A Synthetic Data Toolkit
Published 2024“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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A Survey of Data Clustering Techniques
Published 2023“…Clustering, an unsupervised learning technique, aims to identify a specific number of clusters to effectively categorize the data through data grouping. Hence, clustering is related to many fields and is used in various applications that deal with large datasets. …”
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Hardening the ElGamal cryptosystem in the setting of the second group of units. (c2011)
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Social spider optimization algorithm: survey and new applications
Published 2024“…This survey also studied the main applications of this algorithm in different fields, including medical, mathematical, artificial intelligence, engineering, and data engineering, and how this algorithm affected, impacted, and supported the different fields. …”
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A Tabu Search algorithm for mapping data to multicomputers. (c1997)
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(k, l)-Clustering for Transactional Data Streams Anonymization
Published 2018“…In this paper, we address the correlation problem in the anonymization of transactional data streams. We propose a bucketization-based technique, entitled (k, l)-clustering to prevent such privacy breaches by ensuring that the same k individuals remain grouped together over the entire anonymized stream. …”
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Mining airline data for CRM strategies. (c2006)
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A novel encryption algorithm using multiple semifield S-boxes based on permutation of symmetric group
Published 2023“…The presented algorithm is mainly based on the Shannon idea of substitution–permutation network where the process of substitution is performed by the proposed S<sub>8</sub> semifield substitution boxes and permutation operation is performed by the binary cyclic shift of substitution box transformed data. …”
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…This work aims to enhance the performance of the K-means algorithm by introducing a novel method for selecting the initial centroids, thereby minimizing randomness and reducing the number of iterations needed to reach optimal results. …”
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Physical optimization algorithms for mapping data to distributed-memory multiprocessors
Published 1992“…We also present a technique for efficient mapping of large data sets. The algorithms include a parallel genetic algorithm (PGA), a parallel neural network algorithm (PNN) and a parallel simulated annealing algorithm (PSA). …”
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Properties of simulated annealing and genetic algorithms for mapping data to multicomputers
Published 1997“…We experimentally analyze some properties of simulated annealing algorithms (SA) and genetic algorithms (GA) for mapping data to multicomputers. …”
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
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Parallel physical optimization algorithms for allocating data to multicomputer nodes
Published 1994“…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …”
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
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BioNetApp: An interactive visual data analysis platform for molecular expressions
Published 2019“…BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”
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