Výsledky vyhľadávania - fine-tuning naive Bayesian algorithm

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  1. 1

    Lazy fine-tuning algorithms for naïve Bayesian text classification Autor El Hindi, Khalil M., Aljulaidan, Reem R., AlSalman, Hussien

    ISSN: 1568-4946, 1872-9681
    Vydavateľské údaje: Elsevier B.V 01.11.2020
    Vydané v Applied soft computing (01.11.2020)
    “… In this study, we propose a lazy fine-tuning naïve Bayes (LFTNB) method to address both problems…”
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  2. 2

    A noise tolerant fine tuning algorithm for the Naïve Bayesian learning algorithm Autor Khalil El Hindi

    ISSN: 1319-1578
    Vydavateľské údaje: Springer 01.07.2014
    “…This work improves on the FTNB algorithm to make it more tolerant to noise. The FTNB algorithm augments the Naïve Bayesian (NB…”
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  3. 3

    Building an Ensemble of Fine-Tuned Naive Bayesian Classifiers for Text Classification Autor El Hindi, Khalil, AlSalman, Hussien, Qasem, Safwan, Al Ahmadi, Saad

    ISSN: 1099-4300, 1099-4300
    Vydavateľské údaje: Basel MDPI AG 07.11.2018
    Vydané v Entropy (Basel, Switzerland) (07.11.2018)
    “…Text classification is one domain in which the naive Bayesian (NB) learning algorithm performs remarkably well…”
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  4. 4

    Using differential evolution for fine tuning naïve Bayesian classifiers and its application for text classification Autor Diab, Diab M., El Hindi, Khalil M.

    ISSN: 1568-4946, 1872-9681
    Vydavateľské údaje: Elsevier B.V 01.05.2017
    Vydané v Applied soft computing (01.05.2017)
    “…•Initial population is generated by a method used for fine-tuning the NB, namely, FTNB.•DE algorithm using a multi-parent mutation and crossover operations (MPDE) is proposed…”
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  5. 5

    Fault Detection and Diagnosis Method of Distributed Photovoltaic Array Based on Fine-Tuning Naive Bayesian Model Autor He, Weiguo, Yin, Deyang, Zhang, Kaifeng, Zhang, Xiangwen, Zheng, Jianyong

    ISSN: 1996-1073, 1996-1073
    Vydavateľské údaje: Basel MDPI AG 01.07.2021
    Vydané v Energies (Basel) (01.07.2021)
    “… To this end, a distributed PV array fault diagnosis method based on fine-tuning Naive Bayes model for the fault conditions of PV array such as open-circuit, short-circuit, shading, abnormal…”
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  6. 6

    Fine tuning the tree augmented Naïve Bayes (FTTAN) learning algorithm Autor Alhussan, Amel, El Hindi, Khalil

    Vydavateľské údaje: IEEE 01.11.2015
    “…In this work, we adapt the fine tuning algorithm of Naïve Bayes (NB) for Tree Augmented Naïve Bayes (TAN…”
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  7. 7

    Hemogram data as a tool for decision-making in COVID-19 management: applications to resource scarcity scenarios Autor Avila, Eduardo, Kahmann, Alessandro, Alho, Clarice, Dorn, Marcio

    ISSN: 2167-8359, 2167-8359
    Vydavateľské údaje: United States PeerJ, Inc 29.06.2020
    Vydané v PeerJ (San Francisco, CA) (29.06.2020)
    “… Hemogram exams data from 510 symptomatic patients (73 positives and 437 negatives) were used to model and predict qRT-PCR results through Naïve-Bayes algorithms…”
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  8. 8

    Machine Learning and Deep Learning Algorithms for Skin Cancer Classification from Dermoscopic Images Autor Bechelli, Solene, Delhommelle, Jerome

    ISSN: 2306-5354, 2306-5354
    Vydavateľské údaje: Switzerland MDPI AG 27.02.2022
    Vydané v Bioengineering (Basel) (27.02.2022)
    “…) algorithms tested in this work include logistic regression, linear discriminant analysis, k-nearest neighbors classifier, decision tree classifier and Gaussian naive Bayes, while deep learning (DL…”
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  9. 9

    Multi-label classification of symptom terms from free-text bilingual adverse drug reaction reports using natural language processing Autor Chaichulee, Sitthichok, Promchai, Chissanupong, Kaewkomon, Tanyamai, Kongkamol, Chanon, Ingviya, Thammasin, Sangsupawanich, Pasuree

    ISSN: 1932-6203, 1932-6203
    Vydavateľské údaje: San Francisco Public Library of Science 04.08.2022
    Vydané v PloS one (04.08.2022)
    “… Recently, the effectiveness of machine algorithms in natural language processing (NLP) has been widely…”
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  10. 10

    Probability knowledge acquisition from unlabeled instance based on dual learning Autor Zhao, Yuetan, Wang, Limin, Zhu, Xinyu, Jin, Taosheng, Sun, Minghui, Li, Xiongfei

    ISSN: 0219-1377, 0219-3116
    Vydavateľské údaje: London Springer Nature B.V 01.01.2025
    Vydané v Knowledge and information systems (01.01.2025)
    “…The functionality of machine learning algorithms heavily relies on the abundance and quality of training data accessible…”
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  11. 11

    Deep Embedding Sentiment Analysis on Product Reviews Using Naive Bayesian Classifier Autor Sahithya, Nukabathini Mary Saroj, Prathyusha, Manda, Rachana, Nakkala, Priyanka, Perikala, Jyothi, P. J.

    ISSN: 2456-3307, 2456-3307
    Vydavateľské údaje: 31.03.2019
    “… Deep learning is a class of machine learning algorithms that learn in supervised and unsupervised manners…”
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  12. 12

    Customization of a DADA2-based pipeline for fungal internal transcribed spacer 1 (ITS1) amplicon data sets Autor Rolling, Thierry, Zhai, Bing, Frame, John, Hohl, Tobias M., Taur, Ying

    ISSN: 2379-3708, 2379-3708
    Vydavateľské údaje: United States American Society for Clinical Investigation 11.01.2022
    Vydané v JCI insight (11.01.2022)
    “…Identification and analysis of fungal communities commonly rely on internal transcribed spacer-based (ITS-based) amplicon sequencing. There is no gold standard…”
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  13. 13

    Customization of a dada2-based pipeline for fungal Internal Transcribed Spacer 1 (ITS 1) amplicon datasets Autor Rolling, Thierry, Zhai, Bing, Frame, John V, Hohl, Tobias, Taur, Ying

    ISSN: 2692-8205, 2692-8205
    Vydavateľské údaje: Cold Spring Harbor Cold Spring Harbor Laboratory Press 20.07.2021
    Vydané v bioRxiv (20.07.2021)
    “… the accuracy of sample inference. By fine-tuning quality filtering, we decreased the number of wrongly discarded sequences attributed to Aspergillus species, Saccharomyces…”
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    Paper
  14. 14

    Detecting Textual Propaganda Using Machine Learning Techniques Autor Khanday, Akib Mohi Ud Din, Khan, Qamar Rayees, Rabani, Syed Tanzeel

    ISSN: 2078-8665, 2411-7986
    Vydavateľské údaje: University of Baghdad, College of Science for Women 01.01.2021
    Vydané v Majallat Baghdād lil-ʻulūm (01.01.2021)
    “… In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms…”
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  15. 15

    Applying Deep Belief Networks to Word Sense Disambiguation Autor Wiriyathammabhum, Peratham, Kijsirikul, Boonserm, Takamura, Hiroya, Okumura, Manabu

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 02.07.2012
    Vydané v arXiv.org (02.07.2012)
    “… Then, a separate fine tuning step is employed to improve the discriminative power. We compared DBN with various state-of-the-art supervised learning algorithms in WSD such as Support Vector Machine (SVM…”
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  16. 16

    깊은 신경망 기반 대용량 텍스트 데이터 분류 기술 Autor 조휘열, 김진화, 김경민, 장정호, 엄재홍, 장병탁, Jo, Hwiyeol, Kim, Jin-Hwa, Kim, Kyung-Min, Chang, Jeong-Ho, Eom, Jae-Hong, Zhang, Byoung-Tak

    ISSN: 2383-6318, 2383-6326
    Vydavateľské údaje: 2017
    “… Naïve Bayesian Classifier < Support Vector Machine (SVM) < LSTM < CNN < GRU, in order. The result can be interpreted as follows…”
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  17. 17

    Large-Scale Text Classification with Deep Neural Networks Autor Jo, Hwiyeol, Kim, Jin-Hwa, Kim, Kyung-Min, Chang, Jeong-Ho, Eom, Jae-Hong, Zhang, Byoung-Tak

    ISSN: 2383-6318, 2383-6326
    Vydavateľské údaje: Korean Institute of Information Scientists and Engineers 15.05.2017
    “… Naïve Bayesian Classifier < Support Vector Machine (SVM) < LSTM < CNN < GRU, in order. The result can be interpreted as follows…”
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    Journal Article