Search Results - data distribution ((svm algorithm) OR (((model algorithm) OR (modified algorithm))))

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  1. 1

    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
  2. 2

    Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

    Published 2012
    “…Classification of imbalanced data sets is one of the important researches in Data Mining community, since the data sets in many real-world problems mostly are imbalanced class distribution. …”
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    Thesis
  3. 3

    Classification of imbalanced travel mode choice to work data using adjustable svm model by Qian, Y., Aghaabbasi, M., Ali, M., Alqurashi, M., Salah, B., Zainol, R., Moeinaddini, M., Hussein, E.E.

    Published 2021
    “…This study deals with imbalanced mode choice data by developing an algorithm (SVMAK) based on a support vector machine model and the theory of adjusting kernel scaling. …”
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    Article
  4. 4

    Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

    Published 2024
    “…The sensitivity analyses found the most effective models for predicting HPG for three scenarios using graphical distribution data (Taylor diagram). …”
    Article
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    Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

    Published 2022
    “…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. …”
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    Final Year Project / Dissertation / Thesis
  8. 8

    Stochastic And Modified Sequent Peak Algorithm For Reservoir Planning Analysis Considering Performance Indices by Oskoui, Issa Saket

    Published 2016
    “…In the next stage, the modified Sequent Peak Algorithm (SPA) is employed for the Storage-yield planning analysis of reservoir systems at different demands, reliability and vulnerability performance metrics employing the synthetic streamflow data. …”
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    Thesis
  9. 9

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…The DPA-EHD is further modified by utilizing the pipelining parallelism to reduce the computing iterations and named as data parallel and pipelining algorithm (DPPA-EHD). …”
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    Thesis
  10. 10

    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

    Published 2017
    “…The SD algorithm is employed to balance exploitation and exploration in MSA, thereby resulting in efficient and effective (speed and quality) solution for the APP model. …”
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    Thesis
  11. 11

    Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

    Published 2023
    Subjects: “…Distributed SVM…”
    Conference paper
  12. 12

    A stylometry approach for blind linguistic steganalysis model against translation-based steganography by Mohd Lokman, Syiham

    Published 2023
    “…However, accuracy of blind steganalysis algorithms highly depend on the features selected from the input data especially when attacking embedding techniques in TBS. …”
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    Thesis
  13. 13

    An improvement on the valiantbrebner hypercube data broadcasting technique / Nasaruddin Zenon by Zenon, Nasaruddin

    Published 1990
    “…In section 1.0 a description of the hypercube topological characteristics will be given which can be used to modify the algorithm. Section 2.0 provides the description of the Valiant and Brebner (V-B) algorithm. …”
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    Article
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    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…One of the important assumptions of the linear model is that the error terms are normally distributed. …”
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    Thesis
  16. 16

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
    “…The overall accuracy of the Support Vector Machine SVM and Random Forest RF classifiers revealed that three of the six algorithms exhibited higher ranks in the landslide detection. …”
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    Thesis
  17. 17

    Exploring imbalanced class issue in handwritten dataset using convolutional neural networks and deep belief networks by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Abdullah, Ahmad Zarir

    Published 2016
    “…The experiment shows that although the algorithm is stable and suitable for multiple domains, the imbalanced data distribution still manages to affect the outcome of the model.…”
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    Proceeding Paper
  18. 18

    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia by San, Limhwee

    Published 2006
    “…The developed algorithms are two-band algorithm, terma linear and modified algorithm from the combination of the visible and infrared thermal bands. …”
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    Thesis
  19. 19

    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
    “…This research aims to develop a model for the Modified Internal Rate of Return (MIRR) in long-term investment strategies using the gamma distribution. …”
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    Thesis
  20. 20

    Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior by Ahmed, Al Omari Mohammed

    Published 2013
    “…Subsequently, we use Markov Chain Monte Carlo (MCMC) method in the Bayesian estimator of the Weibull distributionand Weibull regression model with shape unknown. For the Weibull model with right censoring and unknown shape, the full conditional distribution for the scale and shape parameters are obtained via Gibbs sampling and Metropolis-Hastings algorithm from which the survival function and hazard function are estimated. …”
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    Thesis