Search Results - (( pattern machine algorithm ) OR ((( pattern bayes algorithm ) OR ( patterns based algorithm ))))

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  1. 1
    Machine Learning Applications in Offense Type and Incidence Prediction

    Machine Learning Applications in Offense Type and Incidence Prediction by Balaji, R., Manjula Sanjay, Koti, Harprith, Kaur

    Published 2024
    “…We can develop targeted strategies to prevent and respond to such incidents by analyzing these patterns. Artificial Intelligence (AI) techniques encompass variouscomputational methods and algorithms designed to enable machines to perform tasks that typically require human intelligence. …”
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  2. 2
    Evaluation of fall detection classification approaches

    Evaluation of fall detection classification approaches by Kerdegari, Hamideh, Samsudin, Khairulmizam, Ramli, Abdul Rahman, Ghotoorlar, Saeid Mokaram

    Published 2012
    “…This paper presents the comparison of different machine learning classification algorithms using Waikato Environment for Knowledge Analysis (WEKA) platform for classifying falling patterns from ADL patterns. …”
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  3. 3
    Employability prediction based on personality test using Naive Bayes Algorithm / Mohd Alief Mukhlis Mohd Adnin

    Employability prediction based on personality test using Naive Bayes Algorithm / Mohd Alief Mukhlis Mohd Adnin by Mohd Adnin, Mohd Alief Mukhlis

    Published 2020
    “…The purpose of this project was to identify the personality type of person that can be used for employability prediction, to design a prototype model of prediction using Naive Bayes algorithm and to test the functionality the proposed prototype. …”
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  4. 4
    A behavioral trust model for internet of healthcare things using an improved FP-growth algorithm and Naïve Bayes classifier

    A behavioral trust model for internet of healthcare things using an improved FP-growth algorithm and Naïve Bayes classifier by Azad, Saiful, Amin Salem, Saleh Bllagdham, Mahmud, Mufti, Kaiser, M. Shamim, Miah, Md Saef Ullah

    Published 2021
    “…Towards securing these frameworks through an intelligent TMM, this work proposes a machine learning based Behavioral Trust Model (BTM), where an improved Frequent Pattern Growth (iFP-Growth) algorithm is proposed and applied to extract behavioral signatures of various trust classes. …”
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  5. 5
    Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir

    Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

    Published 2019
    “…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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  6. 6
    Identification model for hearing loss symptoms using machine learning techniques

    Identification model for hearing loss symptoms using machine learning techniques by Nasiru Garba Noma

    Published 2014
    “…The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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  7. 7
    Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.]

    Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Warris, Saiful Nizam, Abu Bakar, Mohd Saifulnizam, Kadar, Rozita

    Published 2024
    “…This study has investigated five commonly used machine learning algorithm to be constructed as potential models for predicting stroke dataset. …”
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  8. 8
    An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA

    An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

    Published 2025
    “…However, these algorithms often fall short in consistently detecting and classifying network intrusions, particularly when distinctions between classes are subtle or when facing evolving attack patterns. …”
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  9. 9
    Pixel-based feature for android malware family classification using machine learning algorithms

    Pixel-based feature for android malware family classification using machine learning algorithms by Mohd Zamri, Osman, Rahiwan Nazar, Romli, Ahmad Firdaus, Zainal Abidin, Mohd Faaizie, Darmawan

    Published 2021
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  10. 10
    Android Mobile Malware Classification Based on System Call and Permission Using Tokenization

    Android Mobile Malware Classification Based on System Call and Permission Using Tokenization by Intan Nurfarahin Binti Ahmad

    Published 2024
    thesis::master thesis
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  11. 11
    Household overspending model amongst B40, M40 and T20 using classification algorithm

    Household overspending model amongst B40, M40 and T20 using classification algorithm by Zulaiha Ali, Othman, Azuraliza, Abu Bakar, Nor Samsiah, Sani, Jamaludin, Sallim

    Published 2020
    “…The model development employs five machine learning algorithms namely decision tree, Naive Bayes, Neural network, Support Vector Machines, Nearest Neighbour. …”
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  12. 12
    Naive Bayes-guided bat algorithm for feature selection

    Naive Bayes-guided bat algorithm for feature selection by Taha A.M., Mustapha A., Chen S.-D.

    Published 2023
    Subjects: “…Algorithms…”
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  13. 13
    Classification Of Hand Movements Based On Discrete Wavelet Transform And Enhanced Feature Extraction

    Classification Of Hand Movements Based On Discrete Wavelet Transform And Enhanced Feature Extraction by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…Four popular machine learning algorithms include k-nearest neighbor (KNN), linear discriminate analysis (LDA), Naïve Bayes (NB) and support vector machine (SVM) are used in evaluation. …”
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  14. 14
    Data mining techniques for disease risk prediction model: A systematic literature review

    Data mining techniques for disease risk prediction model: A systematic literature review by Ahmad W.M.T.W., Ghani N.L.A., Drus S.M.

    Published 2023
    Conference Paper
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  15. 15
    An algorithm for Elliott Waves pattern detection

    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…All of the fundamental features of an proper Elliott Wave pattern (EW pattern) are reviewed and explained. Based on this knowledge, an algorithm for detection of these patterns is designed, developed and tested. …”
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  16. 16
    An algorithm for Elliott Waves pattern detection

    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…All of the fundamental features of an proper Elliott Wave pattern (EW pattern) are reviewed and explained. Based on this knowledge, an algorithm for detection of these patterns is designed, developed and tested. …”
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  17. 17
    Suspicious activities detection for anti-money laundering using machine learning techniques

    Suspicious activities detection for anti-money laundering using machine learning techniques by Lim, Aun Chir

    Published 2025
    “…XGBoost is selected as the core detection engine due to its superior performance among five supervised machine learning algorithms tested: Random Forest, Naïve Bayes, Support Vector Machine and Artificial Neural Network. …”
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  18. 18
    Naive bayes-guided bat algorithm for feature selection.

    Naive bayes-guided bat algorithm for feature selection. by Taha, Ahmed Majid, Mustapha, Aida, Chen, Soong Der

    Published 2013
    “…Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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  19. 19
    Car recognition using Bayes Classifier / Nur Atiqah Mat Samadi

    Car recognition using Bayes Classifier / Nur Atiqah Mat Samadi by Mat Samadi, Nur Atiqah

    Published 2017
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  20. 20
    A review on sentiment analysis model Chinese Weibo text

    A review on sentiment analysis model Chinese Weibo text by Dawei Wang, Rayner Alfred

    Published 2020
    “…In word segmentation, related algorithms can be divided into three categories: based on string matching, based on understand and based on statistics [1]. …”
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