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Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis
Published 2017“…Results: By using the ID3 algorithm, it is possible to consider the relationship among variables and to identify the most informative variables for predicting the classification of the instance. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg...
Published 2022“…The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg...
Published 2022“…The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. …”
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Gene Selection For Cancer Classification Based On Xgboost Classifier
Published 2022“…XGBoost Classifier is applied in this research, which it is an efficient open-source implementation of the gradient boosted trees algorithm. Gradient boosting is a supervised learning algorithm, which attempts to accurately predict a target variable by combining the estimates of a set of simplifier, weaker models. …”
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Random forest algorithm for co2 water alternating gas incremental recovery factor prediction
Published 2020“…RF develops multiple decision trees based on the random selection of the input data and random selection of the variables. …”
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Coronary artery stenosis detection and visualization / Tang Sze Ling
Published 2015“…The manual operation of Coronary Artery Disease (CAD) diagnosis from volumetric Computed Tomography Angiography (CTA) is a very time consuming process and lead to inter- and intra-observer variability of the readers. This thesis investigates the computeraided CAD diagnosis in order to reduce reading time and manual operators’ variability. …”
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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…Random Forests (RF) are ensemble of trees methods widely used for data prediction, interpretation and variable selection purposes. …”
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Developing A Prediction Tool To Improve The Shading Efficiency Of The Pedestrian Zones
Published 2020“…The development of the prediction tool was conducted base on integrating three sequenced algorithms, which are sun position algorithm, shadow length and position algorithm, and expansion limit algorithm. …”
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Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network
Published 2010“…The results from the single and multi-transceiver systems showed that the algorithm reduced the length of scheduling up to 43% in the multi-transceiver system and 23% in single-transceiver system. …”
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms
Published 2024“…In this research, machine learning algorithms including regression models, tree regression models, support vector regression (SVR), ensemble regression (ER), and gaussian process regression (GPR) were utilized to predict the compressive and tensile concrete strength. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering
Published 2019“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Hypertension Prediction in Adolescents Using Anthropometric Measurements: Do Machine Learning Models Perform Equally Well?
Published 2022“…However, different machine learning algorithms were utilized in conjunction with various anthropometric data, either alone or in combination with other biophysical and lifestyle variables. …”
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Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi
Published 2012“…In addition, a fast version of the proposed algorithm is presented that reduces the computational budget 46.28% further while maintaining the video quality. …”
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Predictive Modelling of Stroke Occurrence among Patients using Machine Learning
Published 2023“…Advanced machine learning algorithms, including logistic regression, decision trees, random forests, and support vector machines, were utilized to analyses the dataset and develop a predictive model. …”
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Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri
Published 2023“…Dimension reduction algorithm such as LDA and CNN were applied on the spectra to reduce the number of variables to be trained. …”
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