Search Results - learning-((bayes algorithm) OR (((based algorithm) OR (bat algorithm))))

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  1. 1

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

    Published 2013
    “…Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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    Article
  2. 2

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

    Published 2023
    “…Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
    Article
  3. 3

    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…As a conclusion, the MAPE obtained for the Bat Algorithm based Multi-Layer Feedforward Neural Network is 4.79 in %.…”
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    Article
  4. 4

    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…As a conclusion, the MAPE obtained for the Bat Algorithm based Multi-Layer Feedforward Neural Network is 4.79 in %.…”
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    Thesis
  5. 5

    BAT-BP: A new BAT based back-propagation algorithm for efficient data classification by Mohd. Nawi, Nazri, M. Z., Rehman, Hafifi, Nurfarian, Khan, Abdullah, Siming, Insaf Ali

    Published 2016
    “…Training neural networks particularly back propagation algorithm is a complex task of great importance in the field of supervised learning. …”
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    Article
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    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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    Article
  9. 9

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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    Article
  10. 10

    Opposition-Based Quantum Bat Algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters by Islam, J., Meraj, S.T., Masaoud, A., Mahmud, M.A., Nazir, A., Kabir, M.A., Hossain, M.M., Mumtaz, F.

    Published 2021
    “…This study proposes an opposition-based quantum bat algorithm (OQBA) to determine these optimum switching angles. …”
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    Article
  11. 11

    Opposition-Based Quantum Bat Algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters by Islam, J., Meraj, S.T., Masaoud, A., Mahmud, M.A., Nazir, A., Kabir, M.A., Hossain, M.M., Mumtaz, F.

    Published 2021
    “…This study proposes an opposition-based quantum bat algorithm (OQBA) to determine these optimum switching angles. …”
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    Article
  12. 12

    Applying learning to filter text by Sainin, Mohd Shamrie

    Published 2005
    “…The use of probabilistic approaches such as naïve Bayes algorithm is the effective algorithms currently known for learning to filter or classify text document.Naïve Bayes algorithm is one of the algorithms in Machine Learning that manipulates probability estimation or reasoning about the observed data.The growing of bulk e-mail or known as spam e-mail becomes a threat to users’ privacy and network load and in the case of e -mail filtering,naïve Bayes classifier can be trained to automatically detect spam messages.Similar to the e-mail, forum application may be misused by the user to send bad messages and in some extent may offence other readers.Forum filtering may be less important compared to e-mail spam filtering; however there is a possibility of using naïve Bayes to learn the messages and automatically detect bad messages.Most of the forum application found in the web is applying keyword based text filtering which scan the words and change the detected words into certain representation.Instead of defining a set of keywords to filter the forum messages, this paper will explains the experiment in applying a learning to filter text especially in the educational and anonymous forum message, where there is no user registration required to submit messages.…”
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    Conference or Workshop Item
  13. 13

    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

    Published 2021
    “…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. In this paper, single classifiers such as Support Vector Machine, Naïve Bayes, Bayes Net, Decision Stump, k – Nearest Neighbors, Logistic Regression, Multilayer Perceptron and Decision Tree is experimented. …”
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    Final Year Project
  14. 14

    Bat algorithm for rough set attribute reduction by Taha A.M., Tang A.Y.C.

    Published 2023
    “…AR techniques have recently attracted attention due to its importance in many areas such as pattern recognition, machine learning and signal processing. In this paper, a new optimization method has been introduced called bat algorithm for attribute reduction (BAAR), the proposed method is based mainly on the echolocation behavior of bats. …”
    Article
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    Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm by Yusof, Norzihani, Rosidi, Siti Aishah Rosidi, Ibrahim, Nuzulha Khilwani Ibrahim, Ahmed Ali, Ahmed El-Mogtaba Bannga

    Published 2020
    “…From the results, the different value of accuracy for both SVM and Naïve Bayes Algorithm was 2.4%. The Naïve Bayes Algorithm displayed better result comparing to SVM. …”
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    Article
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    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

    Published 2021
    “…In this research, Support Vector Machine (SVM) machine learning detection & prevention algorithm were developed to detect this type of attacks Two other techniques were benchmarked decision tree and Naïve Bayes. …”
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    Article
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    Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour by Pebrianti, Dwi, Ariawan, Angga, Bayuaji, Luhur, Mahdiana, Deni, ,, Rusdah

    Published 2022
    “…The single Classifier test with the Naïve Bayes algorithm produces the highest accuracy value of 72.7%, while using k-NN algorithm is 81.5%. …”
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    Proceeding Paper
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    Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

    Published 2024
    “…Overall, the proposed fuzzy rule-based diabetes diagnosis and level of care fuzzy model works well with most of the machine learning algorithms tested. …”
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    Article
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    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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    Article