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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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Development of a syncope classification algorithm from physiological signals acquired in tilt-table test by Gan, Ming Hong

“…Additionally, stratified 5-fold cross-validation was performed to evaluate the performance of proposed model. Features that selected for the classification is mean of systolic and diastolic blood pressure, standard deviation of real variability of diastolic blood pressure, and the mean of systolic blood pressure in low and high frequency ratio. …”
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Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid by Lorpunmanee, Siriluck, Md Sap, Mohd Noor, Abdullah, Abdul Hanan

“…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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A rule-based image segmentation method and neural network model for classifying fruit in natural environment / Hamirul'aini Hambali by Hambali, Hamirul'aini

“…The result of the NN model shows that, with the network configuration of 6-7-4, the NN model works very well for objects exposed to the natural illumination.To justify our proofof- concept, the proposed segmentation methods and classification model are tested on jatropha fruit images and the results show that the developed methods and model are able to improve the segmentation and classification accuracy, respectively.…”
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Rule-based embedded HMMs phoneme classification to improve Qur’anic recitation recognition by Mohammed Ali Alqadasi, Ammar, Sunar, Mohd Shahrizal, Turaev, Sherzod, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Salam, Md Sah, Alashbi, Abdulaziz Ali Saleh, Ahmed Salem, Ali, Ali, Mohammed A. H.

“…This paper introduces a Rule-Based Phoneme Duration Algorithm to improve phoneme classification in Qur’anic recitation. …”
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K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

“…This research presents a two-phase phishing detection system by employing unsupervised feature selection and supervised classification. In the first phase, the best set of features is identified by the Genetic algorithm and is utilised by the K-means clustering algorithm to divide the dataset into groups with similar traits. …”
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population by Yahaya, Yasmin Arijah Che

“…It gives 97.75% of mean precision, 93.95% of mean sensitivity and 95.7% of mean specificity. …”
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

“…After that cancer-affected region in the lung is segmented with the help of the proposed Butterfly Optimization Algorithm-based K-Means Clustering (BOAKMC) algorithm. …”
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Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

“…The main objective in this study is to determine the better method to be used to find the centres in the Radial Basis Functional Link Nets for data classification. Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim by Mohamad Kasim, Adibah I’zzah

“…The classification process incorporated Root Mean Square (RMS) analysis for feature extraction and multilayer perceptron (MLP) neural networks for pattern recognition. …”
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The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…It was demonstrated from the simulation investigation that the CWT model could yield a better signal transformation amongst the preprocessing algorithms. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…The Fuzzy c-means clustering improved the accuracy of classification task to 40.53%. …”
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Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm by Abdulwahid S., Mahmoud M.A., Abdulwahid N.

A hybrid spiking neural network model for multivariate data classification and visualization. by Ming, Leong Yii, Teh, Chee Siong, Chen, Chwen Jen

“…Empirical studies of the hybrid model using synthetic and benchmarking datasets yielded promising classification accuracy and intuitive rich visualization.…”
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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…For this experiment, the modified word vectors serve as input to train a Machine Learning (ML) model for the text classification process, aiming for the developed ML model to have a significantly smaller parameter count. …”
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Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri by Jafri, Siti Syazwana

“…The chosen technique is classification and the algorithm that will be applied in the classification process is K- Nearest Neighbor (KNN). …”
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The classification of impact signal of 6 DOF cobot by means of machine learning model by Kai, Gavin Lim Jiann, Ahmad Fakhri, Ab Nasir, Anwar, P. P. Abdul Majeed, Mohd Azraai, Mohd Razman, Ismail, Mohd Khairuddin, Li, Lim Thai

“…A grid search approach was used to identify the best hyperparameter for each model. The model with the highest classification accuracy of 95.2% was the MLP model compared to SVM (92.4%) and kNN (79%). …”
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