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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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Book Section -
2
Music Recommender System Using Machine Learning Content-Based Filtering Technique
Published 2022“…These are the popular algorithm for unsupervised learning, a machine learning method to analyse and cluster datasets. …”
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Undergraduates Project Papers -
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Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel
Published 2024“…This research is divided into two phases – 1) Feature Engineering phase explains skin conditions based on lesion segmentation and different dermoscopic feature extraction, while 2) Classification phase detects Melanoma. Multiple deep-learning models are proposed for segmentation. Several imaging, computer vision, and pattern recognition algorithms are employed to describe five dermoscopic features. …”
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Predicting the success of suicide terrorist attacks using different machine learning algorithms
Published 2022“…With an accuracy rate of 98.4% and an AUC-ROC score of 99.9%, the Random Forest classifier was the most accurate among all other algorithms. This model is more trustworthy than previous work and provides a useful comparison between machine learning methods and an artificial neural network because it is less dependent and has a multiclass target feature.…”
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Conference or Workshop Item -
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Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms
Published 2023“…There is a specific proportion between blog features and bloggersâ�� tendency to social, political, and cultural patterns of different countries and nations that create trends among the bloggers in these countries. …”
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Box-jenkins and genetic algorithm hybrid model for electricity forecasting system
Published 2005“…By adopting the GA blind search, the algorithm combines searching techniques and their capabilities to learn about the relationship of the pattern-recognition of the past data. …”
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7
Application of machine learning and artificial intelligence in detecting SQL injection attacks
Published 2024“…Datasets of well-known SQL injection attack patterns and AI/ML models intended for cybersecurity anomaly detection are among the resources underexplored, these findings show the potential for boosting detection capabilities by deploying ML and AI-based security solutions, with some algorithms scoring up to an 80 percent success rate in identifying SQL injections. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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Bridging Mayer’s cognitive theory of multimedia learning and computational thinking in tackling the cognitive load issues among young digital natives : a conceptual framework
Published 2022“…CT refers to the capacity of learners to systematically tackle unstructured tasks focused on four computing concepts such as decomposition, abstraction, pattern recognition, and algorithmic thinking. The purpose of this paper is to study the relationship between CT and Mayer’s Cognitive Theory of Multimedia Learning (CTML) on the cognitive load of the learners. …”
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Classification of cervical cancer using random forest
Published 2022“…Cervical cancer is the second most common cancer among Malaysian women between 15 to 44 although the morbidity and the mortality of cervical cancer have been decreasing in recent years. …”
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Characterization of Multiple Omics Signatures in Relation to Dietary Pattern for in Silico Personalised Colon Cancer Risk Stratification: Study Protocol for a Case-control Study an...
Published 2022“…Multiple endpoints will be analyzed, namely metabolomic signatures, epigenetic marks, inflammatory markers and relationship with dietary patterns will be established. Multiple machine learning models will then be used to develop personalised risk stratification algorithms. …”
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Improving named entity recognition accuracy of gene and protein in biomedical text
Published 2011“…The strength of our proposed approach for recognizing biomedical named entity is based on a Statistical Character-Based Syntax Similarity (SCSS) algorithm which measured similarity between all extracted candidates and the well-known biomedical named entities from a corpus. …”
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Factors with retirement behaviour among retirees and pre-retirees identified with a machine learning method / Muhammad Aizat Zainal Alam
Published 2023“…This study uses 3,067 responses which are then be coupled with a machine learning methodology (ranging from Naïve Bayesian, Generalised Linear Model, Logistic Regression, Artificial Neural Network, Decision Tree, Random Forest, and Gradient Boosted Trees) via RapidMiner Studio to expand the understanding of how categories of wealth and expenditures can affect retirement behaviour, given the increasingly important role of machine learning algorithms within the context of behavioural economics where it has been demonstrated to describe patterns and relationships in behavioural data better than standard statistical analysis. …”
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Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset
Published 2018“…This paper proposes IF-Postdiffset as a new variant in R-Eclat algorithm. This paper also highlights the performance of infrequent mining pattern from the transaction database among different variants of the R-Eclat algorithm regarding its execution time.…”
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An expanded square pattern technique in swarm of quadcopters for exploration algorithm
Published 2017“…We simulate the swarm-based exploration algorithm with expanded square pattern using a VREP simulator. …”
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…An algorithm called Flex (Frequent lexicographic patterns) has been proposed in obtaining a good performance of searching li-equent patterns. …”
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A comparative sales forecast study between supervised and unsupervised learning algorithm on restaurant / Azhar Tamby
Published 2006“…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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Student Project -
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Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia
Published 2019“…The data collected was used to learn the structure of BN via some known algorithms using R programming language. …”
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Art-Integration in Computational Thinking as an Unplugged Pedagogical Approach at A Rural Sarawak Primary School
Published 2020“…Promoting Computational Thinking (CT) in education has become an interest among scholars to develop CT skills to promote critical thinking and problem-solving skills among young people. …”
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