Search Results - (( mobile evaluations _ algorithm ) OR ( data classification methods algorithm ))*

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  1. 1
    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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  2. 2
    Optimizing the performance of mobile malware detection using the indexing rule

    Optimizing the performance of mobile malware detection using the indexing rule by Ahmad I.N., Farida Hazwani Mohd Ridzuan, Madihah Mohd Saudi

    Published 2024
    journal::journal article
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  3. 3
    The classification of wink-based eeg signals by means of transfer learning models

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…The results obtained from the TL-ML pipelines were evaluated in terms of classification accuracy, Precision, Recall, F1-Score and confusion matrix. …”
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  4. 4
    Hybrid intelligent approach for network intrusion detection

    Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

    Published 2015
    “…Clustering is the last step of processing before classification has been performed, using k-means algorithm. …”
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  5. 5
    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control

    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

    Published 2020
    “…Total of ten control methods determined from population and individual data were tested against another 10 healthy persons to evaluate the algorithm performance. …”
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  6. 6
    Human activity and posture classification using smartphone sensors and Matlab mobile

    Human activity and posture classification using smartphone sensors and Matlab mobile by Jamian, Syahirah, Gunawan, Teddy Surya, Kartiwi, Mira, Ahmad, Robiah, Kadir, Kushairy, Nordin, Muhammad Noor

    Published 2022
    “…Activity recognition has been used in various ways as technology has advanced, particularly using a smartphone-based approach. This work aims to evaluate the accuracy of the triaxial accelerometer in the Matlab Mobile and examine the development and performance of the algorithms in identifying human motions on individuals of similar ages and physical appearances. …”
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    Proceeding Paper
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  7. 7
    Framework for pedestrian walking behaviour recognition to minimize road accident

    Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

    Published 2021
    “…Fifthly, the performance of the proposed classification methods is validated and evaluated against multiple scenarios and features. …”
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  8. 8
    Framework for pedestrian walking behaviour recognition to minimize road accident

    Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

    Published 2021
    “…Fifthly, the performance of the proposed classification methods is validated and evaluated against multiple scenarios and features. …”
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  9. 9
    A coverage path planning approach for autonomous radiation mapping with a mobile robot

    A coverage path planning approach for autonomous radiation mapping with a mobile robot by Abd Rahman N.A., Sahari K.S.M., Hamid N.A., Hou Y.C.

    Published 2023
    Article
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  10. 10
    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review

    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2020
    “…Decision tree is an important method in data mining to solve the classification problems. …”
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  11. 11
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Since the 1960s, many algorithms for data classification have been proposed. …”
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  12. 12
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…The experimental results on artificial data sets and real-world data sets (from UCI Repository) show that the new method could improve both the efficiency and accuracy of pattern classification. …”
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  13. 13
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. …”
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  14. 14
    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd

    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
    “…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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  15. 15
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
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  16. 16
    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…There are a lot of feature extraction methods and classification methods for iris classification. …”
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    Monograph
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  17. 17
    An efficient and effective case classification method based on slicing

    An efficient and effective case classification method based on slicing by Shiba, Omar A. A., Sulaiman, Md. Nasir, Mamat, Ali, Ahmad, Fatimah

    Published 2006
    “…The paper also discusses two of common classification algorithms that are used either in data mining or in general AI. …”
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  18. 18
    Logistic regression methods for classification of imbalanced data sets

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

    Published 2012
    “…Thus, both proposed imbalanced LR-based methods is simple and effective for classification of imbalanced data sets and have promising results.…”
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  19. 19
    Application of Optimization Methods for Solving Clustering and Classification Problems

    Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

    Published 2011
    “…Samples in the same cluster have the same label. The aim of data classification is to set up rules for the classification of some observations that the classes of data are supposed to be known. …”
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  20. 20
    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm

    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2021
    “…Text classification is a popular method in data mining. It is utilized to get valuable information from the vast quantity of data. …”
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