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1
Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Practical implications In terms of managerial implications, the findings in this research help to frame the adoption of a more advanced analytical approach to forecasting, using a Machine Learning algorithm, in solving a newsvendor problem. …”
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2
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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3
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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4
Music Recommender System Using Machine Learning Content-Based Filtering Technique
Published 2022“…These algorithms identify hidden patterns or data groupings without the assistance of a human. …”
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5
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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6
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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8
An expanded square pattern technique in swarm of quadcopters for exploration algorithm
Published 2017“…In this algorithm, the expanded square pattern is conducted by a series of distance around a fixed reference point. …”
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9
Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset
Published 2018“…The R-Eclat is a novel algorithm that determines infrequent patterns in the transaction database. …”
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10
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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11
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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12
Using unique-prime-factorization theorem to mine frequent patterns without generating tree
Published 2011“…In this study we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well. …”
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13
Sequential pattern mining using PrefixSpan with pseudoprojection and separator database
Published 2008“…Sequential pattern mining is a new branch of data mining science that solves inter-transaction pattern mining problems. …”
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14
Mining least relational patterns from multi relational tables
Published 2005“…In this paper, we propose an algorithm called Extraction Least Pattern (ELP) algorithm that using a couple of predefined minimum support thresholds. …”
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15
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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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…A comprehensive performance study has been reported that PrefixSpan, one of the sequential pattern mining algorithms, outperforms GSP, SPADE, as well as FreeSpan in most cases, and PrefixSpan integrated with pseudoprojection technique is the fastest among those tested algorithms. …”
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17
The analysis of road traffic fatality pattern for Selangor, Malaysia case study
Published 2021“…The analysed algorithms among others are neural network, random forest, decision tree, logistic regression, naïve Bayes, and support vector machine. …”
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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“…Developing supervised models for cervical cancer is a challenging task. By gleaning deeper insights from the data, data mining knowledge has capability to learn from data, identify the patterns with meaningful in that they lead to some advantages in many real-world applications. …”
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20
Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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