Search Results - (( parallel distribution mining algorithm ) OR ( data implication from algorithm ))
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Random sampling method of large-scale graph data classification
Published 2024“…Mining a large number of graphs becomes a challenging task because state-of-the-art methods are not scalable due to the memory limit. …”
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata
Published 2018“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…The best algorithm will not be the same for all the data sets. …”
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Application Of Bibliometric Analysis on Root Growth Algorithm
Published 2024“…An article reviewed and analyzed bibliographic data on metaheuristics but is not specific on the topic of root growth algorithm. …”
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Malware Classification and Detection using Variations of Machine Learning Algorithm Models
Published 2025“…Types of attacks can be Ping of Death, flooding, remote-controlled attacks, UDP flooding, and Smurf Attacks. Attack data was obtained from the ClaMP dataset, which has an unbalanced data set, and has very high noise, so it is necessary to analyze data packets in network logs and optimize feature extraction which is then analyzed statistically with machine learning algorithms. …”
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Algoritma pendaraban nombor perpuluhan dari perspektif pelajar Tingkatan Satu
Published 2001“…This study discusses the algorithms in multiplication involving decimal numbers from the perspectives of Form One students. …”
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A Method for Mapping XML DTD to Relational Schemas In The Presence Of Functional Dependencies
Published 2008“…To approach the mapping problem, three different components are explored: the mapping algorithm, functional dependency for XML, and implication process. …”
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Age detection from face using Convolutional Neural Network (CNN) / Hanin Hanisah Usok @ Yusoff
Published 2024“…Following a thorough examination of numerous algorithms, CNN was determined to be the best effective method for age recognition from facial features due to its ability to automatically extract important data. …”
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Agreement options for negotiation on material location decision of housing development
Published 2020“…Social implications: The satisficing algorithm of the coalition will satisfy all stakeholders. …”
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Prediction of payment method in convenience stores using machine learning
Published 2023“…The Random Forest algorithm was employed due to its robustness in handling complex, high-dimensional data, and its ability to provide reliable predictions. …”
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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids
Published 2023“…Using felid presence-absence data from three study regions in Southeast Asia (mainland, Borneo and Sumatra), we tested the performances of SDMs by implementing four modelling frameworks: GLM and RF with bootstrapped and non-bootstrapped training data. …”
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Ethical implications of artificial intelligence in nursing care: a systematic literature review from an Islamic perspective
Published 2025“…The synthesis identified three primary ethical themes: 1) Safety, with subthemes of data privacy, misuse, algorithm bias, and physical safety; 2) Human element, focusing on trust, empathy, and human touch; and 3) Autonomy and informed decision-making. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network
Published 2020“…This study used 1,538 data samples from Goldman Osteometric Dataset which consisted of femur, humerus and tibia parts. …”
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Temporal - spatial recognizer for multi-label data
Published 2018“…Hence, there is a need for a recognition algorithm that can separate the overlapping data points in order to recognize the correct pattern. …”
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Smart Agriculture Economics and Engineering: Unveiling the Innovation Behind AI-Enhanced Rice Farming
Published 2024“…To address these challenges, an innovative Artificial Intelligence-based (AI-based) predictive algorithm has been proposed, leveraging the Cross Industry Standard Process for Data Mining (CRISP-DM) data science framework. …”
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