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Prediction of earnings manipulation on Malaysian listed firms: A comparison between linear and tree-based machine learning by Rahman, R.A., Masrom, S., Zakaria, N.B., Nurdin, E., Abd Rahman, A.S.

“…Thus, the aim of the paper is to compare the earnings manipulation prediction models developed by using two types of machine learning algorithms; linear and tree categories. …”
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VEHICLE CLASSIFICATION FROM CCTV IMAGES AND VIDEOS by KAMARUDDIN, ERNA SHAFFIQA

“…The feature extraction obtain is trained using Linear SVM and Decision Trees. The result shows that the Linear SVM algorithm outperform ACF algorithm with accuracy percentage of 88.5% compared to 62.8% for smaller datasets.…”
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Route Optimization System by Zulkifli, Abdul Hayy

“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Tree-based machine learning in classifying reverse migration/ Azreen Anuar, Nur Huzeima Mohd Hussain and Hugh Byrd by Anuar, Azreen, Mohd Hussain, Nur Huzeima, Byrd, Hugh

“…The study compares the performance of three types of treebased machine learning (Decision Tree, Random Forest, Gradient Boosted Trees) with linear-based algorithms (Logistic Regression, Fast Last Margin, Generalized Linear Model). …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

“…This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island by Mohd Shafri, Helmi Zulhaidi, Ramle, F. S. H.

“…The classification using SVM method was implemented automatically by using four kernel types; linear, polynomial, radial basis function and sigmoid. …”
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Optimize class time tabling by using genetic algorithm technique in UTHM by Ahmad, Izah Rafidah

“…This research used genetic algorithm (GA) that was applied to java programming languages with a goal of reducing conflict and optimizing the fitness. …”
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The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari

“…Here, we introduce the similarity distance based on Euclidean distance for circular model and obtain a cluster tree using the single linkage clustering algorithm. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg... by Balogun, A.-L., Tella, A.

“…Correlation analysis and four machine learning algorithms (random forest, decision tree regression, linear regression, and support vector regression) were used to analyze ozone and meteorological dataset in the study area. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg... by Balogun, A.-L., Tella, A.

“…Correlation analysis and four machine learning algorithms (random forest, decision tree regression, linear regression, and support vector regression) were used to analyze ozone and meteorological dataset in the study area. …”
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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

“…As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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Machine learning versus linear regression modelling approach for accurate ozone concentrations prediction by Jumin E., Zaini N., Ahmed A.N., Abdullah S., Ismail M., Sherif M., Sefelnasr A., El-Shafie A.

“…Different Machine Learning algorithms have been investigated, viz. Linear Regression, Neural Network and Boosted Decision Tree. …”

Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite by Suali, Anjila J., Nuraminah Ramli, Rozmie Razif Othman, Hasneeza Liza Zakaria, Iszaidy Ismail, Nor Shahida Mohd Jamail, Rimuljo Hendradi, Nurol Husna Che Rose

“…This study proposes a combinatorial testing method utilizing the Whale Optimization Algorithm (WOA). …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Mapping of Individual Oil Palm Trees Using Airborne Hyperspectral Sensing: An Overview by Jusoff, Kamaruzaman, Pathan, Mubeena

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Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions by Ahmed, Mashuk, Nasser, Abdullah B., Kamal Z., Zamli, Heripracoyo, Sulistyo

“…Metaheuristic algorithms have been used successfully for solving different optimization problems. …”
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Solar radiation prediction using boosted decision tree regression model: A case study in Malaysia by Jumin E., Basaruddin F.B., Yusoff Y.B.M., Latif S.D., Ahmed A.N.

An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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