Search Results - (( data distribution issues algorithm ) OR ( data distribution function algorithm ))

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  1. 1

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. …”
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    Thesis
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    Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

    Published 2016
    “…A popular distribution for the modelling of discrete count data is the Poisson distribution. …”
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    Thesis
  4. 4

    An Optimized Binary Scheduling Controller for Microgrid Energy Management Considering Real Load Conditions by Mannan M., Roslan M.F., Reza M.S., Mansor M., Jern K.P., Hossain M.J., Hannan M.A.

    Published 2024
    “…The controller's aims include minimizing total operating costs for distributed energy resources and solving intricate constraint optimization issues with scheduling management operations. …”
    Conference Paper
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    Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

    Published 2023
    “…Furthermore, the proposed techniques based on the QLearning algorithm do not consider context-based actions. Thus, these techniques are unable to detect failures that occur due to the improper use of context data, which is becoming an increasingly common issue in mobile applications nowadays. …”
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    Thesis
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    Forecasting FTSE Bursa Malaysia KLCI Trend with Hybrid Particle Swarm Optimization and Support Vector Machine Technique by Lee, Zhong Zhen, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Abraham, Ajith

    Published 2013
    “…The SVM algorithm uses the Radial Basis Function (RBF) kernel function and optim ization of the gam ma and large margin parameters are done using the PSO algorithm. …”
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    Conference or Workshop Item
  8. 8

    Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications by Hassan, Amal Soliman, Elsherpieny, Elsayed Ahmed, Mohamed, Rokaya Elmorsy

    Published 2022
    “…Furthermore, the estimation of entropy is an important issue in statistics and machine learning. This study estimated the Rényi and q-entropies of a power-function distribution in the presence of s outliers using classical and Bayesian procedures. …”
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    Article
  9. 9

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…However, by changing the distribution of both classes, the original classes distribution that are followed by that particular data will be violated. …”
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    Thesis
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    Examination invigilation timetable using Genetic Algorithm / Mohamad Fakhrullah Ibrahim by Ibrahim, Mohamad Fakhrullah

    Published 2025
    “…The current manual process is labor-intensive, error-prone, and time-consuming. To overcome these issues, a system utilizing a Genetic Algorithm (GA) was developed to automate and optimize the timetabling process. …”
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    Thesis
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    Modeling The Modified Internal Rate Of Return (Mirr) For Long-Term Investment Strategy By The Assumption Of Gamma Distribution by Sayed, Amani Idris A

    Published 2023
    “…However, simultaneously estimating all three parameters (shape, scale, and growth) through the maximum-likelihood function is computationally complex. Alternative approaches such as the Simulated Annealing (SA) algorithm, which maximizes the log-likelihood function, and Bayesian MCMC estimation are considered. …”
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    Thesis
  14. 14

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…One of the main issues in genetic k-means based algorithms is their sensitivity to outliers and unevenly distributed clusters due to the mean compromised computations. …”
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    Thesis
  15. 15

    Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

    Published 2014
    “…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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    Book Section
  16. 16

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…To evaluate the capability of ROA at addressing complicated problems, it has subjected to experiment several benchmark functions. The ROA has then compared with nine well-known optimization algorithms. …”
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    Thesis
  17. 17

    Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

    Published 2022
    “…Furthermore, the proposed techniques based on the Q-Learning algorithm do not consider context-based actions. Thus, these techniques are unable to detect failures that occur due to the improper use of context data, which is becoming an increasingly common issue in mobile applications nowadays. …”
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    Article
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    Enhancing high-dimensional streaming data analysis: optimizing Online Feature Selection for handling drift using optimization technique and ensemble learning by Kamaru-Zaman, Ezzatul Akmal

    Published 2024
    “…In the era of data-driven decision-making, managing dynamic data streams characterized by evolving data distributions and high dimensionality presents a formidable challenge for online feature selection. …”
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    Thesis
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    Critical insight for MAPReduce optimization in Hadoop by Khan, Burhan ul Islam, Olanrewaju, Rashidah Funke, Altaf, Hunain, Shah, Asadullah

    Published 2014
    “…Numerous applications are being developed for BigData. Achieving an optimal approach for higher performance in terms of efficient load balancing, load distribution, optimum resource utilization, minimum overheads and least possible delay has been the vital issue for cloud infrastructure. …”
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    Article