Search Results - (( age classification modeling algorithm ) OR ( using function based algorithm ))
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…Whilst it was observed that the optimized k-NN model based on the aforesaid pipeline could achieve a classification accuracy of 100% for the training, validation, and tes t data. …”
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The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach
Published 2018“…Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. However, the application of SVM for prediction and classification in specific sport has rarely been used to quantify/discriminate low and high-performance athletes. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators
Published 2019“…Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the significant variables identified. k-NN model variations, i.e., fine, medium, coarse, cosine, cubic and weighted functions as well as logistic regression, were trained based on the significant performance variables. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators
Published 2019“…Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the significant variables identified. k-NN model variations, i.e., fine, medium, coarse, cosine, cubic and weighted functions as well as logistic regression, were trained based on the significant performance variables. …”
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Stress mental health symptom assessment mobile application for young adults
Published 2023“…Before this stage, the KNN algorithm is employed to construct the model using Google Form response data as part of the application development process. …”
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Final Year Project / Dissertation / Thesis -
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The identification of high potential archers based on relative psychological coping skills variables: a support vector machine approach
Published 2018“…Support Vector Machine (SVM) has been revealed to be a powerful learning algorithm for classification and prediction. However, the use of SVM for prediction and classification in sport is at its inception. …”
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Forward scattering radar for real-time detection of human activities and fall classification
Published 2019“…Support Vector Machine (SVM) algorithm modified by kernel linear function was used for classifying the fall event from the other activities. …”
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Modular deep neural network in reducing overfitting to enhance generalization / Mohd Razif Shamsuddin
Published 2024“…Machine Learning (ML) and Artificial Intelligence (AI) are a hype in this new age. Some researcher may use it to do classification, recognitions, or even predictions. …”
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The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach
Published 2018“…Support Vector Machine (SVM) has been revealed to be a powerful learning algorithm for classification and prediction. However, the use of SVM for prediction and classification in sport is at its inception. …”
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Conference or Workshop Item -
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Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population
Published 2023“…Pelvis bone is the most trustworthy part in human body for sex estimation and age classification. In this research, Phenice method will be utilised for the sex estimation and age classification. …”
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Classification of hand gestures from EMG signals / Diaa Albitar
Published 2022“…This study is to develop classification model to classify six hand gestures using Artificial Intelligent algorithm. …”
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VHDL modeling of EMG signal classification using artificial neural network
Published 2012“…A back-propagation neural network with Levenberg-Marquardt training algorithm has been used for the classification of EMG signals. …”
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Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.]
Published 2018“…This paper presents the gait pattern classification between 3 groups which are control, stroke only and stroke with Peripheral Neuropathy (SPN) using k-Nearest Neighbors (kNN) algorithm. …”
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Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…The best model (RF) executed using 5 predictors (Age, TG, creatinine, Troponin and TC). …”
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Poverty risk prediction based on socioeconomic factors using machine learning approach
Published 2025“…The feature that was found to be the most influential predictor of poverty risk was age. These findings imply that Logistic Regression is the suitable and interpretable model that can be used with structured data in the classification of poverty. …”
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Student Project -
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Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data
Published 2014“…Therefore, the work presented here includes embedded hardware system that works with classification algorithm on real EEG signals, in a ubiquitous setting. …”
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Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd...
Published 2024“…This resulted in the highest classification accuracy obtained by Indians, followed by Chinese and Malays in the age groups of 10–12 years and 16–20 years. …”
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