Search Results - (( java implementation tree algorithm ) OR ( using systematic learning algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Loan default prediction using machine learning algorithms: a systematic literature review 2020 -2023 by Soomro, Anam, Zakariyah, Habeebullah, Aftab, S.M.A., Muflehi, Mohamad, Shah, Asadullah, Meraj, Syeda

“…This study conducts a systematic literature review (SLR) on the prediction of loan defaults using machine learning algorithms (MLAs) from 2020 to 2023. …”
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Application of deep learning algorithms in lung sound classification: A systematic review since 2015 by Sundaraj, Kenneth, Neili, Zakaria

“…Using specific keywords combined with deep learning terms, we identified 1428 articles. …”
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Systematic review on missing data imputation techniques with machine learning algorithms for healthcare by Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Maen, Mohd Khaled

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Machine learning algorithms on price and rent predictions in real estate: A systematic literature review / Muhamad Harussani Abdul Salam ... [et al.] by Abdul Salam, Muhamad Harussani, Mohd, Thuraiya, Masrom, Suraya, Johari, Noraini, Mohamad Saraf, Mohamad Haizam

“…This study will provide new insights on the Machine Learning Algorithms in the real estate industry.…”
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A systematic review of machine learning techniques and applications in soil improvement using green materials by Saad, Ahmed Hassan, Nahazanan, Haslinda, Yusuf, Badronnisa, Toha, Siti Fauziah, Alnuaim, Ahmed, El-Mouchi, Ahmed, Elseknidy, Mohamed, Mohammed, Angham Ali

“…The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using a systematic procedure known as PRISMA and meta-analysis. …”
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A Systematic Review Of Machine Learning Algorithms For Mental Health Detection Using Social Media Data by Madina Amiri, Sundresan Perumal, Norita Md. Norwawi, Nurazah Ismail

A systematic review of machine learning techniques and applications in soil improvement using green materials by Saad, Ahmed Hassan, Nahazanan, Haslinda, Yusuf, Badronnisa, Toha, Siti Fauziah, Alnuaim, Ahmed, El-Mouchi, Ahmed, Elseknidy, Mohamed, Mohammed, Angham Ali

“…The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using a systematic procedure known as PRISMA and meta-analysis. …”
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A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting by Md Salleh N.S., Suliman A., Jorgensen B.N.

A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

Assessing the efficacy of machine learning algorithms for syncope classification: A systematic review by Goh, Choon-Hian, Ferdowsi, Mahbuba, Gan, Ming Hong, Kwan, Ban-How, Lim, Wei Yin, Tee, Yee Kai, Rosli, Roshaslina, Tan, Maw Pin *

“…The aims of the study were to systematically evaluate available machine learning (ML) algorithm for supporting syncope diagnosis to determine their performance compared to existing point scoring protocols. …”
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Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: a systematic review by Musri, Nabila, Christie, Brenda, Ichwan, Solachuddin Jauhari Arief, Cahyanto, Arief

“…Studies published from 2015 to 2021 under the keywords (deep convolutional neural network) AND (caries), (deep learning caries) AND (convolutional neural network) AND (caries) were systematically reviewed. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

“…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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Depression Detection Based on Features of Depressive Behaviour Through Social Media Analytic: A Systematic Literature Review by Mat Ripah N.A., Abdul Latif A., Che Cob Z., Mohd Drus S., Md Anwar R., Mohd Radzi H.

“…Furthermore, it is also shown that various machine learning algorithms are used, and the most used are Neural Network and Support Vector Machine. …”

Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance by Alsariera Y.A., Baashar Y., Alkawsi G., Mustafa A., Alkahtani A.A., Ali N.

A Systematic Literature Review of Electricity Load Forecasting using Long Short-Term Memory by Salleh N.S.M., Suliman A., J�rgensen B.N.

Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

“…Furthermore, the taxonomy was used to evaluate the most recent machine learning algorithm and analysis. …”

Educational Data Mining for Student Performance Prediction : A Systematic Literature Review (2015-2021) by Muhammad Haziq, Hassan, Chen, Chwen Jen

“…—This systematic literature review aims to identify the recent research trend, most studied factors, and methods used to predict student academic performance from 2015 to 2021. …”
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