Search Results - (( pattern machine algorithm ) OR ( between training algorithm ))*

Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…Bayesian Optimization optimizes machine learning algorithm hyperparameters to solve this problem. …”
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Zoning map for drought prediction using integrated machine learning models with a nomadic people optimization algorithm by Mohamadi S., Sammen S.S., Panahi F., Ehteram M., Kisi O., Mosavi A., Ahmed A.N., El-Shafie A., Al-Ansari N.

Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms by AbuSalim, S.W.G., Mostafa, S.A., Mustapha, A., Ibrahim, R., Wahab, M.H.A.

“…The algorithms are Decision Tree (c4.5), Linear Regression (LR), and Decision Forest (DF) with a 10-fold cross-validation method for training and testing. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning by Muhammad Ruhul Amin, Shourov, Husman, Muhammad Afif, Toha, Siti Fauziah, Jasni, Farahiyah

“…The inertial sensor data was collected from the smartphone at two different positions and two different orientations. The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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Assessing rainfall prediction models: Exploring the advantages of machine learning and remote sensing approaches by Latif S.D., Alyaa Binti Hazrin N., Hoon Koo C., Lin Ng J., Chaplot B., Feng Huang Y., El-Shafie A., Najah Ahmed A.

“…Statistical models and machine learning algorithms automatically learn and improve based on data. …”

Development of prediction model for phosphate in reservoir water system based machine learning algorithms by Latif S.D., Birima A.H., Ahmed A.N., Hatem D.M., Al-Ansari N., Fai C.M., El-Shafie A.

Current applications of machine learning in dentistry by Ghazali, Ahmad Badruddin, Reduwan, Nor Hidayah, Ibrahim, Roliana

“…The process is similar to a human expert that can learn by repeated training (Hung et al., 2019). The quality of the output depends on the quality of data used to train and validate the algorithm (Rowe, 2019). …”
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Enhancing user authentication through the implementation of the ForestPA algorithm for smart healthcare systems by Nurul Syafiqah, Zaidi, Al Fahim, Mubarak Ali, Ahmad Firdaus, Zainal Abidin, Ibrahim, Adamu Abubakar, Aldharhani, Ghassan Saleh, Mohd Faizal, Ab Razak

“…All these activities are recorded as a dataset for model training. A model was trained via the forest penalizing attributes (ForestPA) algorithm, which can classify profiles into real or fake profiles on the basis of their behavioral patterns. …”
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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

“…Meanwhile, Kmeans clustering algorithm has also been reported has widely known for solving most unsupervised classification problems. …”
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Predicting Cheaters in PlayerUnknown’s Battlegrounds (PUBG) using Random Forest Algorithm by Nurin Alya, Haris

“…The primary goal is to use the Random Forest algorithm, an effective machine learning technique, to predict instances of cheating based on the behavioural patterns of participants. …”
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Handling imbalance visualized pattern dataset for yield prediction by Megat Mohamed Noor, Megat Norulazmi, Jusoh, Shaidah

“…The prediction of the yield outcome in a non close loop manufacturing process can be achieved by visualizing the historical data pattern generated from the inspection machine, transform the data pattern and map it into machine learning algorithm for training, in order to automatically generate a prediction model without the visual interpretation needs to be done by human. …”
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Finger Motion In Classifying Offline Handwriting Patterns by Yeoh, Shen Horng

“…The preprocessed data is classified using the J48 tree algorithm. The correctly classified accuracy prediction after trained could achieve up to 98 %, Finding revealed that the angle of thumbs plays a significant role in classification of the inclination of the English sentence.…”
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Enhancing user authentication through the implementation of the ForestPA algorithm for smart healthcare systems by Zaidi, Nurul Syafiqah, Mubarak Ali, Al-Fahim, Ahmad, Firdaus, Abubakar, Adamu, AlDharhani, Ghassan Saleh, Ab Razak, Mohd Faizal

“…All these activities are recorded as a dataset for model training. A model was trained via the forest penalizing attributes (ForestPA) algorithm, which can classify profiles into real or fake profiles on the basis of their behavioral patterns. …”
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Comprehensive comparison of various machine learning algorithms for short-term ozone concentration prediction by Yafouz A., AlDahoul N., Birima A.H., Ahmed A.N., Sherif M., Sefelnasr A., Allawi M.F., Elshafie A.

SYN Flood detection via machine learning / Muhammad Muhaimin Aiman Mazlan by Mazlan, Muhammad Muhaimin Aiman

“…The core detection and prevention algorithm which is the support vector machine (SVM) were implemented in this project. …”
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DeepIoT.IDS: Hybrid deep learning for enhancing IoT network intrusion detection by A. Mostafa, Salama, Al-Azzawi, Ziadoon Kamil Maseer, Bahaman, Nazrulazhar, Yusof, Robiah, Musa, Omar, Al-rimy, Bander Ali Saleh

“…Recently, researchers have suggested deep learning (DL) algorithms to define intrusion features through training empirical data and learning anomaly patterns of attacks. …”
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Android Mobile Malware Classification Based on System Call and Permission Using Tokenization by Intan Nurfarahin Binti Ahmad

Machine Learning Based Detection for Compromised Accounts on Social Media Networks by K., Swapna, M., Rithika, K., Rukmini, S., Swachitha, Y., Komali

“…Behavioral features include changes in posting frequency, interaction patterns, and location data. We employ machine learning algorithms to train models that can accurately classify accounts as compromised or legitimate based on these features. …”
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Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function by Azma Salwani, Ab Aziz

“…Multi-Layer Perception (MLP) along with batch back propagation algorithm are used. MLP is a gradient descent technique to minimize the error through a particular training pattern in which it adjusts the weight by a small amount at a time. …”
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Comparative analysis of spatio/spectro-temporal data modelling techniques by Abdullah, Mohd Hafizul Afifi, Othman, Muhaini, Kasim, Shahreen

“…Section 3 presents the results of the assessment both SSTD inference-based modelling techniques and data training algorithms, while Section 4 concludes the analysis and ideas for future works.…”
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