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Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman by Abdul Aziz, Maslina, Mustakim, Nurul Ain, Abdul Rahman, Shuzlina

“…The result indicated that the highest accuracy of 89.34% was achieved by the Random Tree algorithm, while the rule-based algorithm PART reached an accuracy of 87.56%. …”
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A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data by Rana, M.M., Rahman, A., Uddin, M., Sarkar, M.R., Shezan, S.A., Ishraque, M.F., Rafin, S.M.S.H., Atef, M.

“…This paper presents a comparative analysis of a categorical variable decision tree algorithm (CVDTA) with the most common peak shaving technique, namely, the general capacity addition technique, to evaluate the peak shaving performance for an IMG system. …”
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Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data by Ong, Song Quan, Pradeep Isawasan, Ahmad Mohiddin Mohd Ngesom, Hanipah Shahar, As’malia Md Lasim, Gomesh Nair

“…Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. …”
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Coronary artery stenosis detection and visualization / Tang Sze Ling by Tang, Sze Ling

“…The manual operation of Coronary Artery Disease (CAD) diagnosis from volumetric Computed Tomography Angiography (CTA) is a very time consuming process and lead to inter- and intra-observer variability of the readers. …”
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Random forest algorithm for co2 water alternating gas incremental recovery factor prediction by Belazreg, L., Mahmood, S.M., Aulia, A.

“…RF develops multiple decision trees based on the random selection of the input data and random selection of the variables. …”
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Optimized Model Inputs Selections for Enhancing River Streamflow Forecasting Accuracy Using Different Artificial Intelligence Techniques by Tofiq Y.M., Latif S.D., Ahmed A.N., Kumar P., El-Shafie A.

Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

Predictive modelling of student academic performance using machine learning approaches : a case study in universiti islam pahang sultan ahmad shah by Nurul Habibah, Abdul Rahman

“…Finally, four models, namely multinomial logistic regression, decision tree, Random Forest, and Naïve Bayes, have perfect scores, 1.00 of area under the receiver operating characteristics curve to distinguish fail grade students. …”
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A new integrated approach for evaluating sustainable development in the electric vehicle sector by Lu, Wen Min, Chou, Chienheng, Ting, Irene Wei Kiong, Liu, Shangming

“…Third, this study uses the classification & regression tree (CART), random forest, and eXtreme gradient boosting (XGBoost) algorithms to assist managers in identifying the key predictive variables for further classification and prediction. …”
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Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

“…The experiment involved five (5) common algorithms: Linear Regressor, Decision Tree Regressor, Random Forest Regressor, Ridge Regressor and Lasso Regressor. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…The sample size was comprised of 55 non-infected trees and 37 infected trees. During the field experiments, oil palm tree samples of non-infected (T0), mild infected (T1), moderate infected (T2), and severe infected (T3) were measured using the FLIR T620 IR infrared thermal imaging camera to obtain the temperature of the oil palm trees. …”
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Detection of phishing websites using machine learning approaches by Farashazillah Yahya, Magnus Anai, Ryan Isaac W Mahibol, Sidney Allister Frankie, Rio Guntur Utomo, Chong Kim Ying, Eric Ling Nin Wei

“…The dataset consists of 11,055 observations and 32 variables. Three supervised learning models are implemented in this study: Decision Tree, K-Nearest Neighbour (KNN), and Random Forest. …”
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Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method by Acharya, U.R., Sudarshan, V.K., Ghista, D.N., Lim, W.J.E., Molinari, F., Sankaranarayanan, M.

“…These features are ranked by using various ranking methods, namely, Bhattacharyya space algorithm, t-test, Wilcoxon test, Receiver Operating Curve (ROC) and entropy. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi by Hosseiny Fatemi, Mohammad Reza

“…H.264/AVC employs variable block-size motion estimation (VBSME) with quarter-pixel accuracy, which significantly improves its coding performance. …”
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Automated diagnosis of diabetes using entropies and diabetic index by Acharya, U.R., Fujita, H., Bhat, S., Koh, J.E.W., Adam, M., Ghista, D.N., Sudarshan, V.K., Chua, K.P., Chua, K.C., Molinari, F., Ng, E.Y.K., Tan, R.S.

“…These redundant features are eliminated by using six feature selection algorithms: Student's t-test, Receiver Operating Characteristic Curve (ROC), Wilcoxon signed-rank test, Bhattacharyya distance, Information entropy and Fuzzy Max-Relevance and Min-Redundancy (MRMR). …”
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The effectiveness of an agile software methodology: empirical evidence on humanistic aspects / Mazni Omar by Omar, Mazni

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