Search Results - (( pattern mining algorithm ) OR ( self ((learning algorithm) OR (learning algorithms)) ))

Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making by Zun, Liang Chuan, Nursultan Japashov, Soon, Kien Yuan, Tan, Wei Qing, Noriszura Ismail

“…Moreover, the introduction of the novel modified stacked ensemble statistical learning-based algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…In this thesis the research of a self-learning algorithm will be presented, outlined and discussed in detailed manner. …”
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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches by Al Mahmud, Suaib, Kamarulariffin, Abdurrahman, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

“…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

“…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
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Development of web based learning content of animation algorithm on searching and sorting techniques / Nur Linda Abdi Nur by Abdi Nur, Nur Linda

“…The objectives of this project is to develop self-learning environment in learning searching and sorting algorithm, enhance understanding of student in learning searching and sorting technique and to apply web-based learning in computer science subject, which focus on courses that use searching and sorting algorithm.…”
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A comparative sales forecast study between supervised and unsupervised learning algorithm on restaurant / Azhar Tamby by Tamby, Azhar

“…In this research, there are two algorithm of neural network will be used. It is coming from supervised and unsupervised learning algorithm. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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Machine learning: tasks, modern day applications and challenges by Aljuaid, Lamyaa Zaed, Koh, Tieng Wei, Sharif, Khaironi Yatim

“…Machine learning algorithms learned from available data. Further, this learning laid the foundation to develop AI for the various systems around us. …”
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Feasibility comparison of HAC algorithm on usability performance and self-reported metric features for MAR learning by Cheng L.K., Selamat A., Zabil M.H.M., Selamat M.H., Alias R.A., Puteh F., Mohamed F., Krejcar O., Herrera-Viedma E., Fujita H.

Contrastive Self-Supervised Learning for Image Classification by Tan, Yong Le

“…Thus, people have introduced a new paradigm that falls under unsupervised learning – self-supervised learning. Through self-supervised learning, pretraining of the model can be conducted without any human-labelled data and the model can learn from the data itself. …”
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Innovating education: AI-powered self-instructional materials for the Moodle platform by Mohd Yatim, Siti Ainor, Ramli, Nurulhuda, Abdul Hamid, Hazrul, Mansor, Mohd Asyraf

“…Designed initially for Open and Distance Learning at Universiti Sains Malaysia, the AI-powered SIM enables self-paced and self-directed learning, catering to diverse learning needs and preferences. …”
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An early warning system for students at risk using supervised machine learning by Yam, Zheng Hong, Mohd Norshahriel, Abd Rani, Nabilah Filzah, Mohd Radzuan, Lim, Huay Yen, Sarasvathi, Nagalingam

“…For that, this study will perform a study of the current issues, factors, and solutions in education student’s data, determine the supervised machine learning algorithms, compare which model is the best predict the students’ performances, develop an early warning system for the educators to make an early decision in order to assist and consult the at-risk students, and finally conduct testing and evaluation of the system. …”
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The use of SOM for fingerprint classification by Turky A.M., Ahmad M.S.

Subjects:

Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

“…This paper proposes a topological clustering algorithm by integrating topological structure and information theoretic learning, i.e., correntropy, into adaptive resonance theory (ART). …”
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An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets by Azlin, Ahmad, Rubiyah, Yusof, Nor Saradatul Akmar, Zulkifli, Mohd Najib, Ismail

“…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

“…Considering the unsupervised learning algorithms, Self-Organizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. …”
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An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

“…Considering the unsupervised learning algorithms, Self­Organizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. …”
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Suicide and self-harm prediction based on social media data using machine learning algorithms by Abdulrazak Yahya, Saleh, Fadzlyn Nasrini, Mostapa

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Novel direct and self-regulating approaches to determine optimum growing multi-experts network structure by Loo, C.K., Rajeswari, M., Rao, M.V.C.

“…SGMN adopts self-adaptive learning rates for gradient-descent learning rules. …”
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An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets by Ahmad, Azlin, Yusof, Rubiyah, Zulkifli, Nor Saradatul Akma, Ismail, Mohd Najib

“…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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