Relevant bibliographies by topics / RapidMiner

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'RapidMiner'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "RapidMiner"

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Sitompul, Noferianto. "Rapid Miner Testing With The Knn Algorithm." Journal Of Data Science 1, no. 02 (2023): 30–36. https://doi.org/10.58471/jds.v1i02.2834.

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In the modern era of computers and the internet, the need for effective data analysis tools is increasing. In the data mining industry, RapidMiner has developed into an essential tool for using simple but effective classification methods such as k-Nearest Neighbors (KNN). The purpose of this study is to evaluate RapidMiner's ability to implement KNN and evaluate its performance on various datasets derived from various characteristics. Test results show that RapidMiner can implement KNN with satisfactory accuracy for most datasets; The methodology used measures classification performance throug
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Dewi, P. S., C. K. Sastradipraja, and D. Gustian. "Sistem Pendukung Keputusan Kenaikan Jabatan Menggunakan Metode Algoritma Naïve Bayes Classifier." Jurnal Teknologi dan Informasi 11, no. 1 (2021): 66–80. http://dx.doi.org/10.34010/jati.v11i1.3593.

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This research aims to build an information system that can support the company in decision-making, especially about the promotion of positions at PT. Global Beautiful Fashion. This is motivated by the difficulty of determining whether or not an employee has been promoted to office, due to an uncomputed system and stacked employee data documents. In this study, the data used is data on the promotion of employee positions at PT. Global Beautiful Clothing and the method used is the Naïve Bayes Classifier algorithm method. And to find out how well the Naïve Bayes Classifier algorithm was used in t
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Shterev, Yordan. "Demo: Using RapidMiner for Text Mining." Digital Presentation and Preservation of Cultural and Scientific Heritage 3 (September 30, 2013): 254–56. http://dx.doi.org/10.55630/dipp.2013.3.33.

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In this demo the basic text mining technologies by using RapidMining have been reviewed. RapidMining basic characteristics and operators of text mining have been described. Text mining example by using Navie Bayes algorithm and process modeling have been revealed.
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Kovács, László, and Hina Ghous. "Efficiency comparison of Python and RapidMiner." Multidiszciplináris Tudományok 10, no. 3 (2020): 212–20. http://dx.doi.org/10.35925/j.multi.2020.3.26.

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Rizqifaluthi, Hafid, and Muhammad Ainul Yaqin. "Process Mining Akademik Sekolah menggunakan RapidMiner." MATICS 10, no. 2 (2019): 47. http://dx.doi.org/10.18860/mat.v10i2.5158.

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<p><strong>Proses mining adalah sebuah ilmu yang</strong></p><strong>dikembangkan dari data mining. Proses mining mengolah data dalam bentuk event logs yang merupakan representasi dari proses bisnis. Jadi jika sebuah perusahaan atau organisasi sudah memiliki sistem informasi yang menyimpan logs secara otomatis, menerapkan proses mining akan mudah dilakukan. Event logs kemudian dipelajari, dimodelkan untuk menemukan ‘proses model’ yang sesuai dengan kejadian-kejadian yang terekam dalam events log</strong>
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Verma, Tanu, Renu Renu, and Deepti Gaur. "Tokenization and Filtering Process in RapidMiner." International Journal of Applied Information Systems 7, no. 2 (2014): 16–18. http://dx.doi.org/10.5120/ijais14-451139.

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Komara, Diemas Arya. "DATA CRAWLING USING RAPIDMINER ON TWITTER." Publication Library and Information Science 6, no. 2 (2023): 48–60. https://doi.org/10.24269/pls.v6i2.6326.

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Twitter is one of the social media that is favored by various groups, Twitter itself can display information in the form of textual information which can be supplemented with videos or images. This study will discuss how to crawl data on Twitter social media, using the Rapidminer application, 10000 data can be retrieved in one operation. This study aims to provide knowledge about how to use Rapidminer programming to obtain data that can later be processed for purposes related to information science. The results of this study are to show how to collect data on Twitter social media quickly using
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Shiva, Asadianfam and Masoud Mohammadi. "IDENTIFY NAVIGATIONAL PATTERNS OF WEB USERS." International Journal of Computer-Aided Technologies (IJCAx) 01, apr (2014): 01–08. https://doi.org/10.5281/zenodo.1423033.

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RapidMiner is a software for machine learning, data mining, predictive analytics, and business analytics. The server will record large web log files when user visits the website. Extracting knowledge from such huge data demands for new methods. In this paper, we propose a web usage mining method with RapidMiner. At first, the redundant files in log file are deleted by Matlab and then we mines web log which has been pretreated with RapidMiner, it obtains the custom of different user to visit the website by processing and analyzing log file, and mines unusual rules, and provides the reference fo
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Noor, Viyan Qomarudin, Raihan Herfiansyah, Arya Syah Ramadhan, and Amali Amali. "Prediksi Diabetes Menggunakan Algoritma Naive Bayes Menggunakan Rapidminer." Pelita Teknologi 19, no. 1 (2024): 16–21. http://dx.doi.org/10.37366/pelitatekno.v19i1.4329.

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Diabetes, the fastest-growing life-threatening disease, presents significant global health challenges, with 3.8 million annual deaths and affecting 422 million individuals worldwide. This study employs RapidMiner, a popular data mining tool, to analyze a public diabetes dataset. Addressing common dataset challenges such as extraneous features, efficient feature selection, and algorithm implementation, the research introduces a novel approach utilizing the Naive Bayes algorithm. Despite inherent complexities, the Naive Bayes model achieves a commendable accuracy rate of 75.51%, showcasing its a
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Fahrullah, Fahrullah, Arbain Arbain, Yeva Bintan, and M. Ari Prayogo. "PENENTUAN KEUTAMAAN KRITERIA PENILAIAN KEBERHASILAN PRAKTEK KERJA LAPANGAN MENGGUNAKAN METODE POHON KEPUTUSAN." Jurnal Komputer dan Teknologi 2, no. 1 (2023): 8–16. http://dx.doi.org/10.58290/jukomtek.v2i1.76.

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Praktek Kerja Lapangan (PKL) merupakan jembatan bagi siswa untuk mengaplikasikan ilmu teoritis yang didapat didalam kelas kemudian diaplikasikan secara nyata didunia kerja. Selama siswa melaksanakan PKL ditempat kerjanya, mereka akan didampingi oleh seorang pembimbing yang berasal dari tempat kerja. Metode Decision Tree (Pohon Keputusan) dapat digunakan untuk menganalisa data siswa terkait dengan pemberian predikat baik atau tidak seorang siswa selama mengikuti PKL. Predikat ini diberikan sebagai pertanggungjawaban moral seorang pembimbing kepada siswa bimbingannya.Kriteria yang digunakan dala
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Dissertations / Theses on the topic "RapidMiner"

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Vašíček, Radek. "Předzpracování dat." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217652.

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This thesis surveys on problems preprocessing data. Forepart deal with view and description characteristic tests for description attributes, methods for work with data and attributes. Second part work describes work with program Rapidminer. It pays pay attention to single functions preprocessing in this programme describes their function. Third part equate to results with using methods preprocessing and without using data preprocessing.
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Stehno, David. "Dolování dat." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-219902.

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The aim of the thesis was to study and describe data mining methodology CRISP-DM. From the collected database of calls to the call center a prediction was performed, based on CRISP-DM methodology. In phase of test situation modeling four different testing methods were used: the k-NN, neural network, linear regression and super vector machine. The input attributes importance for further prediction was evaluated based on different selections. The results and findings may provide data for further more accurate forecasts in the future; not only in number of calls but also other indicators relevant
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Láska, Samuel. "Segmentace struktur mikroskopických dat mozku." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220342.

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This thesis is involved in image processing of medical data and its implementation using Java programming language. The main contribution of this thesis is creation of algorithms for feature extraction from 3D data and subsequent verification of the results for the issue of imagining 3D brain data, and creation of image filters and their implementation in the program RapidMiner. Consequently, the segmentation process is created at the 2D and 3D level, and output of 3D level segmentation are segmented brain structures. Furthermore, segmentation algorithms were compared on the basis of the final
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Patera, Jan. "Rozhodovací stromy." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217653.

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This diploma thesis presents description on several algorithms for decision trees induction and software RapidMiner. The first part of the thesis deals with partition and terminology of decision trees. There’re described all algorithms for decision tree construction in RapidMiner. The second part deals with implementation and comparison of chosen algorithms. The application was developed in C++. Based on the real datesets the comparisson of different algorithms was realized using Rapid Miner 4.0.
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Stříteský, Radek. "Sémantické rozpoznávání komentářů na webu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-317212.

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The main goal of this paper is the identification of comments on internet websites. The theoretical part is focused on artificial intelligence, mainly classifiers are described there. The practical part deals with creation of training database, which is formed by using generators of features. A generated feature might be for example a title of the HTML element where the comment is. The training database is created by input of classifiers. The result of this paper is testing classifiers in the RapidMiner program.
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Nocar, Jan. "Investiční možnosti obyvatel v ČR." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-76224.

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This thesis discusses the options households have when it comes to investing in capital markets in the Czech Republic. The issue of investing and capital market options is analyzed. Following this analysis comes the description of financial instruments, their characteristics, and the usability of these instruments by small investors. On the basis of the theory presented, a study was conducted to examine the usage of individual financial products. The collected data was processed using modern software tools, which helped in drawing several conclusions, results, and recommendations for investors
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Černý, Ján. "Implementace procedur pro předzpracování dat v systému Rapid Miner." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-193216.

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Knowledge Discovery in Databases (KDD) is gaining importance with the rising amount of data being collected lately, despite this analytic software systems often provide only the basic and most used procedures and algorithms. The aim of this thesis is to extend RapidMiner, one of the most frequently used systems, with some new procedures for data preprocessing. To understand and develop the procedures, it is important to be acquainted with the KDD, with emphasis on the data preparation phase. It's also important to describe the analytical procedures themselves. To be able to develop an extentio
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Matuš, Martin. "Predikce výsledků hokejových utkání pomocí data mining modelu." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-193929.

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This thesis focuses on creation and comparison of ice hockey matches prediction models with the view on ice hockey world championship matches. The first part is dedicated to collecting theoretical knowledge needed for solving this problem and the second to applying this set of knowledge. The model creation approach is intertwined with the CRISP-DM data mining methodology, which also defines several chapters of this work. As input data for the models I used performance statistics of individual ice hockey players -- this brought me to implementing a script capable of automatic downloading and ag
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Gonçalves, Leandro Tavares. "Perspectivas e metodologias de pesquisa da Comunicação Social no contexto da internet com o Big Data e da especialização Data Scientist." Universidade Metodista de São Paulo, 2014. http://tede.metodista.br/jspui/handle/tede/723.

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Made available in DSpace on 2016-08-03T12:30:10Z (GMT). No. of bitstreams: 1 Leandro Tavares2.pdf: 1287442 bytes, checksum: 7f5aa84748d1a824abe72b2b6940ffe2 (MD5) Previous issue date: 2014-09-09<br>The work analyzes the media in the context of the Internet and outlines new methodologies for the study area in filtering meanings in the scientific realm of information flows from social networks, news media or any other device that allows storage and retrieval of structured information and unstructured. In an attempt to reflect on the ways that these information flows and develop mainly in the v
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Mašek, Jan. "Detekce objektů v obraze s pomocí Haarových příznaků." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219794.

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This thesis deals with the image object detection using Haar--like features and AdaBoost algorithm. The text describes methods how to train and test an object detector. The main contributon of this thesis consists in creation image object detector in Java programming language. Created algorithms were integrated as plugin into the RapidMiner tool, which is widely used and known worldwide as tool for data mining. The thesis contains the instructions for created operators and few exaples for executing in RapidMiner tool. The functionality of image object detector was demonstrated on selected medi
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Books on the topic "RapidMiner"

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Hofmann, Markus, and Ralf Klinkenberg, eds. RapidMiner. Chapman and Hall/CRC, 2016. http://dx.doi.org/10.1201/b16023.

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RapidMiner. Betascript Publishing, 2010.

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Exploring Data with Rapidminer. Packt Publishing, Limited, 2013.

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Ufuk Çelik, Eyüp Akçetin, Murat Gök. Rapidminer ile Uygulamali Veri Madenciligi. Pusula Yayincilik, 2017.

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Exploring Data With Rapidminer Explore Understand And Prepare Real Data Using Rapidminers Practical Tips And Tricks. Packt Publishing Limited, 2013.

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Ramjan, Sarawut. Principles and Theories of Data Mining with RapidMiner. IGI Global, 2023.

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Ramjan, Sarawut, and Sunkpho. Principles and Theories of Data Mining with RapidMiner. IGI Global, 2023.

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Ramjan, Sarawut, and Jirapon Sunkpho. Principles and Theories of Data Mining with RapidMiner. IGI Global, 2023.

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Ramjan, Sarawut, and Jirapon Sunkpho. Principles and Theories of Data Mining with RapidMiner. IGI Global, 2023.

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Ramjan, Sarawut, and Jirapon Sunkpho. Principles and Theories of Data Mining with RapidMiner. IGI Global, 2023.

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Book chapters on the topic "RapidMiner"

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Anandarajan, Murugan, Chelsey Hill, and Thomas Nolan. "Learning-Based Sentiment Analysis Using RapidMiner." In Practical Text Analytics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95663-3_15.

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Blachnik, Marcin, and Mirosław Kordos. "Information Selection and Data Compression RapidMiner Library." In Studies in Big Data. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30315-4_12.

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Nanda, Adhish, and Aman Jatain. "Analysis of Breast Cancer Detection Techniques Using RapidMiner." In Proceedings of International Conference on Artificial Intelligence and Applications. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4992-2_1.

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Gentile, Anna Lisa, Sabrina Kirstein, Heiko Paulheim, and Christian Bizer. "Extending RapidMiner with Data Search and Integration Capabilities." In The Semantic Web. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47602-5_33.

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Sheth, Neha, Rohan Agrawal, and Santosh Kumar Vishwakarma. "A Content-Based Music Recommendation System Using RapidMiner." In Intelligent Computing Techniques for Smart Energy Systems. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0252-9_36.

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Nandal, Rainu, Anisha Chawla, and Kamaldeep Joshi. "Opinion Mining and Analysing Real-Time Tweets Using RapidMiner." In Advances in Intelligent Systems and Computing. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-4538-9_22.

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Boranbayev, Askar, Gabit Shuitenov, and Seilkhan Boranbayev. "The Method of Analysis of Data from Social Networks Using Rapidminer." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52246-9_49.

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Graczyk, Magdalena, Tadeusz Lasota, and Bogdan Trawiński. "Comparative Analysis of Premises Valuation Models Using KEEL, RapidMiner, and WEKA." In Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04441-0_70.

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Sharma, Akhilesh K., and Prakash Ramani. "Rigorous Data Analysis and Performance Evaluation of Indian Classical Raga Using RapidMiner." In Advances in Intelligent Systems and Computing. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5687-1_9.

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Windarto, Agus Perdana, and Tutut Herawan. "K-Means Algorithm with Rapidminer in Clustering School Participation Rate in Indonesia." In Lecture Notes in Electrical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4597-3_70.

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Conference papers on the topic "RapidMiner"

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Nasution, Nurliana, S. Surmayanti, Sepsa Nur Rahman, Annisak Izzaty Jamhur, and Riandana Afira. "Classification using C4.5 algorithm and rapidminer." In SCIENCE AND TECHNOLOGY RESEARCH SYMPOSIUM 2022. AIP Publishing, 2024. http://dx.doi.org/10.1063/5.0231473.

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Pawar, Tanuj, Parul Kalra, and Deepti Mehrotra. "Relevance Feedback on Mobile Data Using RapidMiner." In 2018 4th International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT). IEEE, 2018. http://dx.doi.org/10.1109/icatcct44854.2018.9001969.

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Alsaqer, Alaa F., and Sreela Sasi. "Movie review summarization and sentiment analysis using rapidminer." In 2017 International Conference on Networks & Advances in Computational Technologies (NetACT). IEEE, 2017. http://dx.doi.org/10.1109/netact.2017.8076790.

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Pawar, Tanuj, Parul Kalra, and Deepti Mehrotra. "Analysis of Sentiments for Sports data using RapidMiner." In 2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT). IEEE, 2018. http://dx.doi.org/10.1109/icgciot.2018.8752989.

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Ye, Dongxiu. "Association Analysis of Supermarket Products Based on RapidMiner." In 5th International Conference on Social Sciences and Economic Development (ICSSED 2020). Atlantis Press, 2020. http://dx.doi.org/10.2991/assehr.k.200331.054.

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Han, Jianchao, Juan C. Rodriguez, and Mohsen Beheshti. "Diabetes Data Analysis and Prediction Model Discovery Using RapidMiner." In 2008 Second International Conference on Future Generation Communication and Networking (FGCN). IEEE, 2008. http://dx.doi.org/10.1109/fgcn.2008.226.

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Kitcharoen, Nopparoot, Sasithorn Kamolsantisuk, Reenapat Angsomboon, and Tiranee Achalakul. "RapidMiner framework for manufacturing data analysis on the cloud." In 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE). IEEE, 2013. http://dx.doi.org/10.1109/jcsse.2013.6567336.

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Mohammed, Osama, Sabah Mohammed, Jinan Fiaidhi, Simon Fong, and Tai-hoon Kim. "Clinical Narratives Context Categorization: The Clinician Approach using RapidMiner." In Sensor and Its Applications 2014. Science & Engineering Research Support soCiety, 2014. http://dx.doi.org/10.14257/astl.2014.51.30.

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Kalra, Vaishali, and Rashmi Aggarwal. "Importance of Text Data Preprocessing & Implementation in RapidMiner." In The First International Conference on Information Technology and Knowledge Management. PTI, 2018. http://dx.doi.org/10.15439/2017km46.

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Shabtari, Morteza Mohammad, Vinod Kumar Shukla, Harendra Singh, and Ipseeta Nanda. "Analyzing PIMA Indian Diabetes Dataset through Data Mining Tool ‘RapidMiner’." In 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE). IEEE, 2021. http://dx.doi.org/10.1109/icacite51222.2021.9404741.

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