Search Results - data distribution ((((some algorithm) OR (tree algorithm))) OR (model algorithm))

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  1. 1
    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari

    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

    Published 2015
    “…We develop the clustering-based procedure for the predicted and residual values obtained from the Down and Mardia model fit of a circular-circular data set. Here, we introduce a measure of similarity based on the circular distance and obtain a cluster tree using the single linkage clustering algorithm. …”
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  2. 2
    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation

    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation by Lateh, Masitah bdul

    Published 2020
    “…Next, samples are generated from Normal Distribution. To test the effectiveness of the proposed algorithm, the real and generated samples is added to training phase to build a prediction model using M5 Model Tree. …”
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  3. 3
    Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids

    Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

    Published 2023
    “…Species Distribution Models (SDMs) are a powerful tool to derive habitat suitability predictions relating species occurrence data with habitat features. …”
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  4. 4
    Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization

    Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization by Hussain Mohammad Yousef Abu Dalbouh

    Published 2024
    thesis::doctoral thesis
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  5. 5
    E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm

    E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik

    Published 2022
    “…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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  6. 6
    Dynamic replication algorithm in data grid: Survey

    Dynamic replication algorithm in data grid: Survey by K. Madi, Mohammed, Hassan, Suhaidi

    Published 2008
    “…In this paper, we present a survey of some related previous works and highlight some various algorithms that have been proposed by other researchers. …”
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  7. 7
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…This model relies mainly on dimensionality reduction and machine learning algorithms. …”
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  8. 8
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

    Published 2022
    “…This model relies mainly on dimensionality reduction and machine learning algorithms. …”
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  9. 9
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…This model relies mainly on dimensionality reduction and machine learning algorithms. …”
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  10. 10
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2022
    “…This model relies mainly on dimensionality reduction and machine learning algorithms. …”
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  11. 11
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2023
    “…This model relies mainly on dimensionality reduction and machine learning algorithms. …”
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  12. 12
    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data

    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Zarir, Abdullah Ahmad

    Published 2018
    “…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 conventional machine learning algorithms.…”
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  13. 13
    Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data

    Area-based vs tree-centric approaches to mapping forest carbon in Southeast Asian forests from airborne laser scanning data by David A. Coomes, Michele Dalponte, Tommaso Jucker, Gregory P. Asner, Lindsay F. Banin, David F.R.P. Burslem, Simon L. Lewis, Reuben Nilus, Oliver L. Phillips, Phua, Mui How, Lan Qie

    Published 2017
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  14. 14
    Appliance level stand-by burst forecast modelling using machine learning techniques

    Appliance level stand-by burst forecast modelling using machine learning techniques by Mustafa, Abid

    Published 2020
    “…This work proposes a technique to model power consumption data and presents a comparative study of five different machine learning algorithms to study their suitability to forecast an appliance's state and standby burst. …”
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  15. 15
    The Performance of Chlorophyll-a Distribution Estimation by Using Ratio Algorithm on Landsat-8 in Sungai Merbok Estuary / Jesse Vince Rabing ... [et al.]

    The Performance of Chlorophyll-a Distribution Estimation by Using Ratio Algorithm on Landsat-8 in Sungai Merbok Estuary / Jesse Vince Rabing ... [et al.] by Rabing, Jesse Vince, Abd.Aziz, Khairul Naim, Kamaruddin, Sharir Aizat, Roslani, Muhammad Akmal, Tajam, Jamil, Ahmad, Aziani, Nazri, Rosnani, Zainol, Zamzila Erdawati, Ramli, Rohayu, Shaari, Mohd Idrus

    Published 2022
    “…The distribution models generated from the algorithms were utilizing Landsat-8 satellite images with B-G and B-R bands ratio. …”
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  16. 16
    A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data

    A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

    Published 2013
    “…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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  17. 17
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    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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  18. 18
    Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching

    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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  19. 19
    An intelligent DDoS attack detection tree-based model using Gini index feature selection method

    An intelligent DDoS attack detection tree-based model using Gini index feature selection method by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik, Atigh, Hayate El

    Published 2023
    “…Our system achieved an overall accuracy of 98, outperforming baseline models that used more advanced algorithms such as Random Forest and XGBoost. …”
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  20. 20
    White root disease auto-detection system for rubber trees based on dynamic electro-biochemical latex properties / Mohd Suhaimi Sulaiman

    White root disease auto-detection system for rubber trees based on dynamic electro-biochemical latex properties / Mohd Suhaimi Sulaiman by Sulaiman, Mohd Suhaimi

    Published 2019
    “…These measurement input were then went through the process of classification in ANN to generate the most optimized models by using LM and SCG algorithm. There were seven optimized models selected out of 336 models generated from the classification process. …”
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