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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

“…Consequently, optimization algorithms including binary gravitation search algorithm (BGSA) and binary particle swarm optimization (BPSO), were employed to identify the optimal channels for gender classification. …”
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Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting by Ali, Noor Rasidah, Ku Mahamud, Ku Ruhana

“…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
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Classification of Cognitive Frailty in Elderly People from Blood Samples using Machine Learning by Idris, S., Badruddin, N.

“…A total of 7 different classification algorithms were used to predict between 6 levels of CF, the Robust and Non-Robust groups, as well as the Robust and Frail with MCI groups. …”
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Segmentation Assisted Object Distinction For Direct Volume Rendering by Irani, Arash Azim Zadeh

“…A set of image processing techniques are creatively employed in the design of K-means based hybrid segmentation algorithm.…”
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The identification of oreochromis niloticus feeding behaviour through the integration of photoelectric sensor and logistic regression classifier by Mohamad Radzi, Mohd Sojak, Mohd Azraai, Mohd Razman, Anwar, P. P. Abdul Majeed, Rabiu Muazu, Musa, Ahmad Shahrizan, Abdul Ghani, Ismed, Iskandar

“…The signals acquired from the sensors are converted into binary data. The hunger behaviour classes are determined through k-means clustering algorithm, i.e., satiated and unsatiated. …”
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Enhanced extreme learning machine for general regression and classification tasks by Mahmood, Saif F

“…The method is developed for regression task by using mean/ median of ELM training errors which is then used as threshold for separating the training data and converting the continuous targets to binary. …”
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Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing by Ramadhan, Rakhmat Sani

“…This research concerns on binary classification which is classified into two classes. …”
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An Optimized Semantic Segmentation Framework for Human Skin Detection by Huong, Audrey, Ngu, Xavier

“…The model produced satisfactory performances even with a strict split of 50 %, confirming the high efficiency of the proposed framework. The mean Jaccard index and Dice similarity measures evaluated between the annotated and predicted mask ranged from 0.80 to 0.93 in the binary classification of pixels as “skin” versus “background”. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

“…However, their performance is slightly inferior to that of support vector machines for binary classification of chemical structures into drug and non drug compounds.…”
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Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection by Jia, Liu

“…Additionally, standard deviation and proposed adaptive K-means algorithms have been employed to minimize the generated rules by ANFIS from the proposed hybrid models. …”
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An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa by Md Isa, Amalina Izzati

“…Inclusive with the design of UFLS is a new module referred as Load Shedding Module (LSM). Two new algorithms i.e., Load Classification based Fuzzy Logic (LCFL) and Binary Evolutionary Programming (BEP) are introduced in the module. …”
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Assessment of predictive models for chlorophyll-a concentration of a tropical lake. by Malek, S., Syed Ahmad, S. M., Singh, S. K., Milow, P., Salleh, A.

“…RMSE is based on the level of error of prediction whereas AUC is based on binary classification task. CONCLUSIONS: Overall, HEA produced the best performance in terms of RMSE, r, and AUC values. …”
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Assessment of predictive models for chlorophyll-a concentration of a tropical lake. by Syed Ahmad Abdul Rahman, Sharifah Mumtazah, Malek, Sorayya, Kashmir Singh, Sarinder Kaur, Milow, Pozi, Salleh, Aishah

“…RMSE is based on the level of error of prediction whereas AUC is based on binary classification task. CONCLUSIONS: Overall, HEA produced the best performance in terms of RMSE, r, and AUC values. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Ensemble Feed-Forward Neural Network and Support Vector Machine for Prediction of Multiclass Malaria Infection by Jimoh, Rasheed Gbenga, Abisoye, Opeyemi Aderiike, Uthman, Muhammed Mubashir Babatunde

“…Globally, recent research are focused on developing appropriate and robust algorithms to provide a robust healthcare system that is versatile and accurate. …”
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A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

“…The first layer is used to detect up to superfamily and family in SCOP hierarchy, by using optimized binary SVM classification rules directly to ROC-Area. …”
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A semi-automated requirements prioritisation technique for scalable requirements with stakeholder quantification and prioritisation by Hujainah, Fadhl Mohammed Omar

“…Furthermore, the proposed SRPTackle is based on the combination of the proposed StakeQP technique, the constructed requirement priority value formulation function and the employing of classifying algorithm (K-means and K-means++) and binary search tree. …”
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Near infrared palm image acquisition and two-finger valley point-based image extraction for palm vascular pattern detection by Mohd Noh, Zarina

“…The biometric recognition process was done by extraction of vascular line features by Local Binary Pattern (LBP), and classification by K-nearest neighbour (KNN) algorithm using cross-validation technique. …”
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