Search Results - (( evaluate information selection algorithm ) OR ( java implication based algorithm ))

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  1. 1

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Thus, this thesis has developed and evaluated a filter based Information Theoretic-based Feature Selection (IFS) for machine learning. …”
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    Thesis
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    An evaluation of feature selection technique for dendrite cell algorithm by Mohamad Mohsin, Mohamad Farhan, Hamdan, Abdul Razak, Abu Bakar, Azuraliza

    Published 2014
    “…In this study, six feature selection algorithms namely Information Gain, Gain Ratio, Symmetrical Uncertainties, Chi Square, Support Vector Machine, and Rough Set with Genetic Algorithm Reduct are examined and their effectiveness to represent dendrite cell signal are evaluated. …”
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  3. 3

    An Improved Action Key Frames Extraction Algorithm for Complex Colour Video Shot Summarization by Mizher, Manar Abduljabbar Ahmad, Ang, Mei Choo, Sheikh Abdullah, Siti Norul Huda, Kok, Weng Ng

    Published 2019
    “…The evaluation results showed that the Improved AKF algorithm achieved better compression ratio and retained sufficient information in the extracted action key frames under different testing video shots. …”
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    Article
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    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…The proposed algorithm has been evaluated using 24 benchmark functions. …”
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    Article
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    Hybrid group decision making method based on multi-granular information using fusion algorithms and consistent fuzzy preference relation / Siti Amnah Mohd Ridzuan by Mohd Ridzuan, Siti Amnah

    Published 2017
    “…Both algorithm been illustrated in textbook selection. The proposed methods can be utilized as another option to solve a decision making problem.…”
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    Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

    Published 2023
    “…The Friedman test result is presented for the performance rank of six benchmark feature selection algorithms and FESSIC algorithm. The Man-Whitney U test is then performed to statistically evaluate the significance difference of the second rank and FESSIC algorithms. …”
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    Rabbit breed classification using CNN / Aishah Nabila Mohd Zaid by Mohd Zaid, Aishah Nabila

    Published 2024
    “…The research methodology encompasses preliminary study, design and implementation, and evaluation phases. Literature review, knowledge acquisition, and dataset collection inform algorithm selection and dataset validation. …”
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    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

    Published 2024
    “…It involves identifying and isolating relevant information from the images that classification algorithms can use to distinguish between different fruit categories. …”
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    Article
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    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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    Article
  17. 17

    Design of intelligent Qira’at identification algorithm by Kamarudin, Noraziahtulhidayu

    Published 2017
    “…A combination of Principal Component Analysis (PPCA) and Gaussian Mixture Model (GMM) is proposedly in used for the classification phase as it is able to reduce any redundancy from the latent variables and carries only the most important information through dispersion of entropy. To evaluate the algorithm, 350 samples for 10 types of Qira’at recitation are in used, and for justifying the best pattern classification, few algorithms are tested in the early preliminary evaluation with K-Nearest Neighbour, GMM and PPCA. …”
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    An ensemble feature selection method to detect web spam by Oskouei, Mahdieh Danandeh, Razavi, Seyed Naser

    Published 2018
    “…With regard to increasing available information in virtual space and the need of users to search, the role of search engines and used algorithms are important in terms of ranking. …”
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    Hybrid performance measures and mixed evaluation method for data classification problems by Hossin, Mohammad

    Published 2012
    “…First, this study examines the use of accuracy measure as a discriminator for building an optimized Prototype Selection (PS) algorithm. Second, this study evaluates the current evaluation practices for evaluating and comparing the two performance measures. …”
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    Thesis