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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…Using metrics, this study evaluates Random Forest, ElasticNet, and Decision Tree algorithms. …”
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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition
Published 2007“…Motivating by these drawbacks, this research proposes a new model of dialogue act recognition in which dynamic Bayesian machine learning is applied to induce dynamic Bayesian networks models from task-oriented dialogue corpus using sets of lexical cues selected automatically by means of new variable length genetic algorithm. …”
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Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. …”
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Classification of heart disease with machine learning: a comparison of grid search, random search, and Bayesian Optimization
Published 2026“…This study systematically evaluates the effect of hyperparameter optimization on the performance of predictive models by comparing three main techniques: Grid Search, Random Search, and Bayesian Optimization. Four commonly used machine learning algorithms: Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Gradient Boosting were tested on benchmark datasets from the UC Machine Learning Repository. …”
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AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING
Published 2021“…The encryption algorithms are playing an important part in the protection level for data. …”
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E4ML: Educational Tool for Machine Learning
Published 2003“…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka
Published 2024“…By using the same dataset, which is downloaded from UCI, Machine Learning Repository, various algorithms used in classification and clustering in this simulation has been analysed comparatively. …”
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Bayesian Network Classifiers for Damage Detection in Engineering Material
Published 2007“…The methodology used in the thesis to implement the Bayesian network for the damage detection provides a preliminary analysis used in proposing a novel fea- ture extraction algorithm (f-FFE: the f-folds feature extraction algorithm). …”
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif
Published 2016“…Prediction in data mining is among the popular machine learning techniques as a part of intelligent techniques, for example, Bayesian methods, neural network, support vector machine, association rule mining, k-nearest-neighbor, rough sets and fuzzy logic. …”
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Research Reports -
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Bayesian Network of Traffic Accidents in Malaysia
Published 2019“…With the advent of technology and the wide application of machine learning algorithm, this goal can be achieved through the Bayesian network analysis, in which it is a directed acyclic probabilistic graphical model. …”
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Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…A useful property of the statistical classifier like Bayesian is that, it is optimal in the sense that it minimizes the expected mis classification rate. …”
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works
Published 2023Conference Paper -
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Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications
Published 2022“…The Bayesian estimators were computed empirically using a Monte Carlo simulation based on the Gibbs sampling algorithm. …”
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Implementation of (AES) Advanced Encryption Standard algorithm in communication application
Published 2014“…Internet communication has become more common in this modern world recently, and one of the important algorithms used is ABS algorithm. However, most of the users have inadequate knowledge and understanding regard to this algorithm implementation in the communication field, as well as the level of security and accuracy will be questioned by the users because of the necessary to maintain the confidentiality of particular data transferred. …”
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A comparative analysis of predicting heart disease using machine learning algorithms
Published 2026“…This study applies six machine learning algorithms, including K-nearest neighbors, logistic regression, Bayesian classifier, decision tree, random forest, and support vector machine. …”
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Predictive modelling of nanofluids thermophysical properties using machine learning
Published 2021“…The optimization of the machine learning parameters was conducted using the Genetic Algorithm or the Bayesian Optimization Algorithm techniques. …”
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