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Classification of Rheumatoid Arthritis using Machine Learning Algorithms by Sharon, H., Elamvazuthi, I., Lu, C.K., Parasuraman, S., Natarajan, E.

“…In this preliminary work, ensemble algorithms such as bagging, AdaBoost and random subspace with base classifier such as random forest and SVM were trained and tested using the assessment criteria such as accuracy, precision, sensitivity and AUC using Weka tool. …”
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Classification of Rheumatoid Arthritis using Machine Learning Algorithms by Sharon, H., Elamvazuthi, I., Lu, C.K., Parasuraman, S., Natarajan, E.

“…In this preliminary work, ensemble algorithms such as bagging, AdaBoost and random subspace with base classifier such as random forest and SVM were trained and tested using the assessment criteria such as accuracy, precision, sensitivity and AUC using Weka tool. …”
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Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms by Haw, Jia Yong, Mohd Yousof, Mohd Fairouz, Abd Rahman, Rahisham, Talib, Mohd Aizam, Azis, Norhafiz

“…However, there are times where the produce of stray gassing event might lead to fault indication in the transformer. Machine learning algorithms are used to classify the DGA data into normal condition and corresponding faults based on IEEE limits and Duval pentagon method. …”
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VGG16-based deep learning architectures for classification of lung sounds into normal, crackles, and wheezes using Gammatonegrams by Zakaria, Neili, Sundaraj, Kenneth

“…In this study, we conducted a comparison of two versions of the VGG16-based deep learning model for breathing sound classification using Gammatonegrams as input. …”
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Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

“…In this research, two categories of eye’s images which are the normal, and the abnormal (i.e. CA) are used. The normal eye, dataset are taken from the eye database (i.e. …”
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Cardiotocogram Data Classification using Random Forest based Machine Learning Algorithm by Molla, M. M. Imran, Jui, Julakha Jahan, Bari, Bifta Sama, Rashid, Mamunur, Hasan, Md Jahid

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An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks by Ihsanto, Eko, Ramli, Kalamullah, Sudiana, Dodi, Gunawan, Teddy Surya

“…Due to the non-stationary nature of the ECG signal, it is rather challenging to use traditional handcraft methods, such as time-based analysis of feature extraction and classification, to pave the way for machine learning implementation. …”
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Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak by Abd Razak, Hana'

“…Towards achieving better detection in real-time environment, colour pixel-based images were trained on five pre-trained CNNs using transfer learning algorithm. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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Improved normalization and standardization techniques for higher purity in K-means clustering by Dalatu, Paul Inuwa, Fitrianto, Anwar, Mustapha, Aida

“…Based on its simplicity, the K-means algorithm has been used in many fields. …”
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Deep learning-based item classification for retail automation by Ling, Ji Xiang

“…This project focuses on developing a deep learning-based system for retail item classification. …”
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Detection on ambiguous software requirements specification written in malay using machine learning by Zahrin, Mohd Firdaus

“…As the result, the Random Forest algorithm is the best algorithm which is measured based on measurement metric i.e. …”
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Application Of Neural Network In Malaria Parasites Classification by Lim, Chia Li

“…Multilayer Perceptron (MLP) network and Radial Basis Function (RBF) network will be developed using MATLAB in which MLP network is trained with Back Propagation, Bayesian Rule and Levenberg-Marquardt learning algorithm and RBF network is trained with k-means clustering algorithm. …”
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Simultaneous fault diagnosis based on multiple kernel support vector machine in nonlinear dynamic distillation column by Taqvi, S.A.A., Zabiri, H., Uddin, F., Naqvi, M., Tufa, L.D., Kazmi, M., Rubab, S., Naqvi, S.R., Maulud, A.S.

“…In the developed MK-SVM algorithm, multilabel approach based on various kernel functions has been utilized for the classification of simultaneous faults. …”
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Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural by Saidin, Mohammad Norrish

“…The optimum value of epoch and hidden nodes for each learning algorithm are determined based on the highest accuracy obtained during training phases. …”
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Converged Classification Network For Matching Cost Computation by Hamid, Mohd Saad, Abd Manap, Nurulfajar, Hamzah, Rostam Affendi, Kadmin, Ahmad Fauzan

“…Overall quantitative results for the proposed work performed competitively compared to other established stereo matching algorithm based on the Middlebury standard benchmark online system.…”
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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

“…However, the training datasets usually compose feature sets of irrelevant or redundant information, which impacts the performance of classification, and traditional learning algorithms such as backpropagation suffer from known issues, including slow convergence and the trap of local minimum. …”
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Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm by Acharya, U.R., Faust, O., Molinari, F., Sree, S.V., Junnarkar, S.P., Sudarshan, V.

“…These classification algorithms are trained using the features extracted from the patient data in order for them to learn the relationship between the features and the end-result (FLD present or absent). …”
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Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

“…For BrC detection, an efficient and reliable model namely Ensemble BrC Detection Network (EBrC-Net) and three misclassification reduction (McR) algorithms are developed. The proposed EBrC-Net model is based on deep learning (DL) based approach. …”
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Neural network paradigm for classification of defects on PCB by Heriansyah, Rudi, Syed Al-Attas, Syed Abdul Rahman, Zabidi, Muhammad Mun'im Ahmad

“…A new technique is proposed to classify the defects that could occur on the PCB using neural network paradigm. The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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