Gotowe bibliografie tematyczne / NaiveBayes

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Gotowa bibliografia na temat „NaiveBayes”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "NaiveBayes"

Arip Rahman Hakim and Achmad Udin Zailani. "SISTEM PERPUSTAKAAN BERBASIS WEB SMPN 226 JAKARTA DAN PENGOPTIMALAN PENCARIAN DENGAN NAIVEBAYES." JURNAL SATYA INFORMATIKA 7, no. 02 (2023): 93–104. http://dx.doi.org/10.59134/jsk.v7i02.175.

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Perpustakaan adalah perpustakaan dikenal sebagai sebuah koleksi besar yang dibiayai dan dioperasikan oleh sebuah kota atau institusi. Demikian halnya di lembaga pendidikan formal seperti sekolah, perpustakaan merupakan sarana wajib yang harus ada.Tetapi tidak semua sekolah mempunyai senuah sistem informasi yang dapat menyimpan dan mencatat pengolahan data buku. Berdasarkan hal itu penulis mencoba membuat sistem informasi yang mudah digunakan dengan berbasis website dan database. Tujuan dari penelitian ini adalah merancang sistem informasi perpustakaan dan menerapkan klasifikasi Naive Bayes unt

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Özdemir, Abdulkadir, Uğur Yavuz, and Fares Abdulhafidh Dael. "Performance evaluation of different classification techniques using different datasets." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 3584. http://dx.doi.org/10.11591/ijece.v9i5.pp3584-3590.

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<span>Nowadays data mining become one of the technologies that paly major effect on business intelligence. However, to be able to use the data mining outcome the user should go through many process such as classified data. Classification of data is processing data and organize them in specific categorize to be use in most effective and efficient use. In data mining one technique is not applicable to be applied to all the datasets. This paper showing the difference result of applying different techniques on the same data. This paper evaluates the performance of different classification te

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Abdulkadir, Özdemir, Yavuz Uğur, and Abdulhafidh Dael Fares. "Performance evaluation of different classification techniques using different datasets." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 3584–90. https://doi.org/10.11591/ijece.v9i5.pp3584-3590.

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Nowadays data mining become one of the technologies that paly major effect on business intelligence. However, to be able to use the data mining outcome the user should go through many processes such as classified data. Classification of data is processing data and organize them in specific categorize to be use in most effective and efficient use. In data mining one technique is not applicable to be applied to all the datasets. Many data users wasting a lot of time trying many classification techniques in order to find the most an appropriate technique to be used. This paper showing the differe

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Mohaddes Deylami, Hanif, and Yashwant Prasad Singh. "Cybercrime detection techniques based on support vector machines." Artificial Intelligence Research 2, no. 1 (2012): 1. http://dx.doi.org/10.5430/air.v2n1p1.

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This paper presents the cybercrime detection model by using support vector machines (SVMs) to classify social network (Facebook) dataset. We try to compare between three kinds of classification algorithms such as: SVMs, AdaBoostM1, and NaiveBayes in order to find a high percentage of classification accuracy. Finally, we conclude SVMs as the best classification algorithm, which uses different breeds of kernel functions in order to improve the classification accuracy on Facebook dataset. Besides, we are using the Weka 3.7.4 software to evaluate classifiers on Facebook dataset.

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孔, 梦秋. "Research on the Classification of Manufacturing Performance Evaluation in Guizhou Based on NaiveBayes Model." Advances in Applied Mathematics 08, no. 12 (2019): 2062–71. http://dx.doi.org/10.12677/aam.2019.812237.

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Sun, Pei Pei, Quan Yin Zhu, Lei Zhou, and Yong Jun Zhang. "Comparative Analysis of Text Categorizer on Science and Technology Intelligence." Applied Mechanics and Materials 530-531 (February 2014): 502–5. http://dx.doi.org/10.4028/www.scientific.net/amm.530-531.502.

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In order to more effectively classify the science and technology intelligence text, the idea that classifying science and technology intelligence text categorization based on different classifiers is proposed. The experiment is done with two thousand Chinese texts based on three different classifiers in this paper. Among these classifiers, the rate of correctly classified instances with NaiveBayes Classifier is 96.95 percent and J48 Classifiers is 97.59. The highest of three classifiers is SMO Classifier and its correct rate is 98.65 percent. According to the analysis of experimental results,

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Rubio Delgado, Elayne, Lisbeth Rodríguez-Mazahua, José Antonio Palet Guzmán, et al. "Analysis of Medical Opinions about the Nonrealization of Autopsies in a Mexican Hospital Using Association Rules and Bayesian Networks." Scientific Programming 2018 (2018): 1–21. http://dx.doi.org/10.1155/2018/4304017.

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This research identifies the factors influencing the reduction of autopsies in a hospital of Veracruz. The study is based on the application of data mining techniques such as association rules and Bayesian networks in data sets obtained from opinions of physicians. We analyzed, for the exploration and extraction of the knowledge, algorithms like Apriori, FPGrowth, PredictiveApriori, Tertius, J48, NaiveBayes, MultilayerPerceptron, and BayesNet, all of them provided by the API of WEKA. To generate mining models and present the new knowledge in natural language, we also developed a web applicatio

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K P, Mamatha. "Customer Feedback Analysis Using Facial Emotion Recognition." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31022.

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Our lives are being significantly impacted by the rapid development of wireless technology and mobile gadgets on this day. The digital economy demands that services be developed almost instantly while also paying close attention to client feedback. It becomes difficult to manage and analyze the information gathered about products from customers. Also, everyone is not intended to provide clear feedback whether the product was satisfactory or not. It is a very difficult and time- consuming task to analyze the data collected manually. To proceed with the problem and through much research we came

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Maia, Luiz Cláudio, and Renato Rocha Souza. "Uso de sintagmas nominais na classificação automática de documentos eletrônicos." Perspectivas em Ciência da Informação 15, no. 1 (2010): 154–72. http://dx.doi.org/10.1590/s1413-99362010000100009.

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Esta pesquisa verificou se ocorre aprimoramento na classificação de documentos eletrônicos com o uso de técnicas e algoritmos de mineração de texto (análise de texto) utilizando-se, além das palavras, sintagmas nominais como indexadores. Utilizaram-se duas ferramentas nos experimentos propostos desta pesquisa o OGMA e a WEKA. O OGMA foi desenvolvido pelos autores para automatizar a extração dos sintagmas nominas e o cálculo do peso de cada termo na indexação dos documentos para cada um dos seis métodos propostos. A WEKA foi utilizada para analisar os resultados encontrados pelo OGMA utilizando

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Seimahura, Syarah, and Arina Selawati. "ANALISIS PERBANDINGAN KLASIFIKASI CITRA MYCROBACTERIUM TUBERCULOSIS." Akrab Juara : Jurnal Ilmu-ilmu Sosial 7, no. 1 (2022): 311. http://dx.doi.org/10.58487/akrabjuara.v7i1.1777.

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Tuberculosis (TB) is an infectious disease that remains a challenging health problem worldwide. This disease is caused by rod-shaped bacteria called Mycobacterium tuberculosis. These bacteria usually affect the lungs but can also spread to other parts of the body such as the eyes, bones and blood vessels. It was reported that around. 4.74 million new TB cases were identified and around eight hundred thousand people died from TB, during 2015 in Southeast Asia. In this study, color image segmentation techniques were carried out using classification methods by comparing several methods including

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Rozprawy doktorskie na temat "NaiveBayes"

Komara, Akhilandeswari. "Aspect Mining of COVID-19 Outbreak with SVM and NaiveBayes Techniques." Thesis, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-21891.

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The outbreak of COVID-19 is one of the major pandemics faced by the world ever and the World Health Organization (WHO) had declared it as the deadliest virus outbreak in recent times. Due to its incubation period, predicting or identifying the paints had become a tough job and thus, the impact is on a large scale. Most of the countries were affected with Coronavirus since December 2019 and the spread is still counting. Irrespective of the preventive measures being promoted on various media, still the speculations and rumors about this outbreak are peaks, that too particular with the social med

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Części książek na temat "NaiveBayes"

Guo, Hang, and Lizhu Zhou. "A Framework for Titled Document Categorization with Modified Multinomial Naivebayes Classifier." In Advanced Data Mining and Applications. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73871-8_31.

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Kumar, C. Sathish, B. Sathees Kumar, Gnaneswari Gnanaguru, V. Jayalakshmi, S. Suman Rajest, and Biswaranjan Senapati. "Augmenting Chronic Kidney Disease Diagnosis With Support Vector Machines for Improved Classifier Accuracy." In Advances in Medical Technologies and Clinical Practice. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-5946-4.ch024.

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Mitigating chronic kidney disease poses a substantial challenge to the healthcare community. This study assesses diverse classification algorithms, encompassing NaiveBayes, multi-layer perceptron, and support vector machine. The analysis involves scrutinizing the chronic kidney disease dataset from the UCI machine learning repository. Techniques like replacing missing values, unsupervised discretization, and normalization are employed for precision enhancement. The empirical results of the classification models are evaluated for accuracy and computational time. The conclusive observation indic

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Streszczenia konferencji na temat "NaiveBayes"

Duarte, Jaisson, and Edimar Manica. "Aplicação de mineração de dados para identificação de possíveis inadimplentes em uma cooperativa do ramo agrícola." In Escola Regional de Banco de Dados. Sociedade Brasileira de Computação - SBC, 2024. http://dx.doi.org/10.5753/erbd.2024.238844.

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A inadimplência é um problema que afeta tanto os consumidores quanto as empresas, comprometendo o crédito e gerando prejuízos financeiros. Estudos recentes revelam a preocupante situação do Brasil nesse contexto. Além disso, as cooperativas do ramo agropecuário também enfrentam desafios em relação à inadimplência, uma vez que lidam com transações financeiras e têm um grande número de clientes, o que dificulta a avaliação de crédito. Neste artigo, é descrito o desenvolvimento de um modelo de classificação capaz de identificar os clientes com maiores chances de inadimplência. O modelo combina os

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