Search Results - (( model validation from algorithm ) OR ( early classification system algorithm ))

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

“…Training and testing data in the study used a mixed model, namely data division, split model and cross validation. …”
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Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

“…High accuracy shows the capability of the classification model to correctly predict the G. boninense detection while high F1-score indicates that the classification is able to validate the detection of G. boninense correctly with low misclassification rate. …”
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Imbalanced multi-class power transformer fault data classification through Edited Nearest Neighbour-Manhattan-Random Forest by R Azmira, Putri Azmira

“…This misclassification and data loss can lead to the failure to detect rare but critical transformer faults, jeopardizing system reliability and early fault mitigation. To address this challenge, the study focuses on improving Edited Nearest Neighbour techniques using alternative distance measures to enhance classification accuracy in imbalanced dissolved gas analysis datasets. …”
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Diabetic retinopathy detection using Gray-Level Co-Occurrence Matrix / Aliff Azfar Aris by Aris, Aliff Azfar

“…The classification was performed by using Support Vector Machine (SVM) to generate the cross-validation accuracy to determine the learning algorithm’s performance. …”
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Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application by Aminordin, Azmi

“…In increasing the reliability, the results obtained are then validated by using statistical analysis procedure which each machine learning classification algorithm are iterate 50 times. …”
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Deep learning-based recommendation system to address challenges in providing electronic services by AL Hinai, Turki Abdullah Masood, Al Kulaibi, Juma, Al Husaini, Mohammed Abdulla Salim, Al Husaini, Yousuf Nasser, Habaebi, Mohamed Hadi

“…Furthermore, 10-fold cross-validation was employed to assess model generalizability, yielding accuracy scores ranging from 0.88 to 0.92, with Fold 4 scoring 0.89623. …”
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All-in-1 adverse drug reaction reporting system / Long Chiau Ming … [et al.] by Chiau Ming, Long, Karuppannan, Mahmathi, Abdul Wahab, Izyan, Abd Wahab, Mohd Shahezwan, Zulkifly, Hanis Hanum

“…Probability is assigned via a score termed definite, probable, possible or doubtful. Values obtained from this algorithm are used in peer reviews to verify the validity of reporter’s conclusion regarding ADRs. …”
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Identifying the correct articulation point of a Quranic letters of the throat (al-halqu) makhraj by Othman, Ahmad Al Baqir, Ahmad, Salmiah, Badron, Khairayu, Altalmas, Tareq M. K.

“…Data was trained using an improved deep learning Convolutional Neural Network (CNN) classification model. Results shows that the algorithm was able to detect the letters produced at throat area, which are also known as Izhar Halqi letters. …”
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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

“…For this purpose, the dataset was randomly split into three sets, 60.0% for model training, 20.0% for model validating, and 20.0% for model testing. …”
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Human hearing disorder recognition model using eeg-aep based signal by Md Nahidul, Islam

“…The experimental outcomes demonstrated that traditional machine learning and CNN algorithms achieved comparatively lower accuracy than the proposed model. …”
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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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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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