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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System by Al-Hameli, Bassam Abdo, Alsewari, Abdulrahman A., Alraddadi, Abdulaziz Saleh, Aldhaqm, Arafat

“…The proposed method has three steps: preprocessing, feature selection and classification. Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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Bee colony optimisation of the travelling salesman problem in light rail systems by Wang, Chen, Leong, Kah Huo, Abdul-Rahman, Hamzah

“…The study reported in this paper aimed to identify the most efficient algorithm and develop a mathematical model based on artificial bee colony optimisation to solve this problem in light rail transit systems. …”
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LSSVM parameters tuning with enhanced artificial bee colony by Mustaffa, Zuriani, Yusof, Yuhanis

“…The proposed model was employed in predicting financial time series data and comparison is made against the standard Artificial Bee Colony (ABC) and Cross Validation (CV) technique.The simulation results assured the accuracy of parameter selection, thus proved the validity in improving the prediction accuracy with acceptable computational time.…”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Chong, Hou Ming, Yin Yap, Xien, Seng Chia, Kim

“…In implementing an automation plantation system, a plant health classification system is necessary in monitoring the health of the plants. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…In implementing an automation plantation system, a plant health classification system is necessary in monitoring the health of the plants. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…In implementing an automation plantation system, a plant health classification system is necessary in monitoring the health of the plants. …”
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Using convolution neural networks for improving customer requirements classification performance of autonomous vehicle by Hao, Wang, Asrul, Adam, Fengrong, Han

“…As the results, the accuracy of CNN classification has improved at least 6 percent compared to the conventional algorithms.…”
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Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…FID3 algorithm combined the fuzzy system and decision tree techniques with ID3 algorithm as the decision tree learning. …”
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Accuracy and performance analysis for classification algorithms based on biomedical datasets by Al-Hameli, Bassam Abdo, Alsewari, Abdulrahman A., Khubrani, Mousa, Fakhreldin, Mohammoud

“…The study suggests finding a classifier among the most common kinds of classification algorithms within a combined approach represent in Bayesian, Trees, Rules, Function, and lazy algorithms to automate a better performance of early detection of diseases from the medical datasets. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…In implementing an automation plantation system, a plant health classification system is necessary in monitoring the health of the plants. …”
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A preliminary lightweight random forest approach-based image classification for plant disease detection by Mashitah Ibrahim, Muzaffar Hamzah, Mohammad Fadhli Asli

“…Random Forest is a special kind of ensemble learning technique and it turns out to perform very well compared to other classification algorithms such as Support Vector Machines (SVM) and Artificial Neural Networks (ANN). …”
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Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

“…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
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Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months by Suarin, Nur Aisyah Syafinaz, Chia, Kim Seng, Mohamad Fuzi, Siti Fatimah Zaharah

“…Thus, this study aims to evaluate the feasibility of homogenous transfer learning approaches to overcome data constraints in developing NIRS predictive models of stingless bee honey qualities across different months. …”
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Early autism spectrum disorder detection using machine learning / Muhammad Shahmi Shahron Nizan by Shahron Nizan, Muhammad Shahmi

“…The project follows a modified waterfall approach, focusing on creating a user-friendly interface and integrating the Random Forest Classification Algorithm for accurate detection. The results show the algorithm's impressive performance with an 86% precision in predicting ASD traits. …”
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Ganoderma boninense disease detection by near-infrared spectroscopy classification: a review by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Fatimah, Dzaharudin, Chalermwisutkul, Suramate, Akkaraekthalin, Prayoot

“…This review describes past and future prospects of integrated research of near-infrared spectroscopy (NIRS), machine learning classification for predictive analytics and signal processing towards an early G. boninense detection system. …”
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An early warning detection system of terrorism in indonesia from Twitter contents using naïve bayes algorithm by Aryuni, Mediana, Miranda, Eka, Fernando, Yudi, Kibtiah, Tia Mariatul

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Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

“…Therefore, reliable network operations are a factor that needs to be considered to prevent attacks as early as possible in order to avoid more severe system damage. …”
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

“…An automatic and accurate system for detection DR signs can significantly help ophthalmologists to make best decision for early treatment thus reducing risk of vision loss. …”
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Automated and high accuracy out-of-hospital heart diseases early detection system by Hussein, Ahmed Faeq, Hashim, Shaiful Jahari, Abdul Aziz, Ahamd Fazli, Rokhani, Fakhrul Zaman, Wan Adnan, Wan Azizun

“…The high accuracy together with the automated capability of the system can help detect heart problems at the early stages even before the patients pay visit to the hospital.…”
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