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Development of a Prediction Algorithm using Boosted Decision Trees for Earlier Diagnoses on Obstructive Sleep Apnea by Sim, Doreen Ying Ying

“…This research develops a knowledge-based system by using computational intelligent approaches based on Boosting algorithms on decision trees augmented by pruning techniques and Association Rule Mining. …”
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Modeling forest fires risk using spatial decision tree by Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin, Sitanggang, Imas Sukaesih

“…This paper presents our initial work in developing a spatial decision tree using the spatial ID3 algorithm and Spatial Join Index applied in the SCART (Spatial Classification and Regression Trees) algorithm. …”
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Reinforcement Learning Algorithm for Optimising Durian Irrigation Systems: Maximising Growth and Water Efficiency by Ramli, Muhammad Shahrul Azwan, Zainal Abidin, Mohamad Shukri, Hasan, Nor Shahida, Md Reba, Mohd Nadzri, Kolawole, Keshinro Kazeem, Ardiansyah, Rizqi Andry, Mpuhus, Sikudhan Lucas

“…This study presents a Reinforcement Learning-based algorithm designed to optimise irrigation for Durio Zibethinus (i.e., durian) trees, aiming to maximise tree growth and reduce water usage. …”
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Extended spatial decision tree algorithm for classifying hotspot occurrence by Sitanggang, Imas Sukaesih

“…This work proposes a new spatial decision tree algorithm namely the extended spatial ID3 decision tree algorithm to classify hotspots occurrence from a forest fires dataset that contains point, line and polygon features. …”
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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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Footwear quality evaluation using decision tree and logistic regression models by Tan, Swee Choon

“…The objectives of the study are to determine the rank factors that affect the quality of footwear using decision tree methods. …”
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Cancer Prediction Based On Data Mining Using Decision Tree Algorithm by Loh, Kin Ming

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Random forest algorithm for co2 water alternating gas incremental recovery factor prediction by Belazreg, L., Mahmood, S.M., Aulia, A.

“…The optimum developed model consists of 60 decision trees with a maximum depth of seven (7). …”
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A comparison of decision tree, logistic regression, artificial neural network and random forest algorithms to predict suicidal ideation among young adults in Malaysia by Chan, Sin Yin, Ch’ng, Chee Keong

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Development of trees management system using radial basis function neural network for rain forecast by Auzani, Hasnul, Hashim, Khairusy Syakirin Has-Yun, Mohd Nazri, Farah Aniza

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Sales prediction of religious product and services of Mutawwif Haramain Travel & Tours using predictive analytics by Mohd Sabri, Nurul Ainin Qistina

“…This research develops a predictive model for sales prediction at Mutawwif Haramain Travel & Tours, utilizing machine learning algorithms, specifically Decision Tree, Random Forest, and Naive Bayes, to uncover patterns in customer behavior and seasonal demand. …”
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Reverse migration prediction model based on machine learning / Azreen Anuar by Anuar, Azreen

“…For this purpose, three (3) algorithms have been assessed, namely, the Random Forest, Decision Tree, and Gradient Boosted Tree. …”
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Classification model for hotspot occurrences using a decision tree method by Sitanggang, Imas Sukaesih, Ismail, Mohd Hasmadi

“…This work demonstrates the application of a decision tree algorithm, namely the C4.5 algorithm, to develop a classification model from forest fire data in the Rokan Hilir district, Indonesia. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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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. …”

Machine learning in predicting anti-money laundering compliance with protection motivation theory among professional accountants by Masrom, S., Tarmizi, M.A., Halid, S., Rahman, R.A., Abd Rahman, A.S., Ibrahim, R.

“…The research elaborates on the design and implementation of machine learning models based on three algorithms: Decision Tree, Gradient Boosted Tree, and Support Vector Machine. …”
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Application of Decision Tree Algorithm for Predicting Monthly Pan Evaporation Rate by Abed M., Imteaz M.A., Ahmed A.N., Huang Y.F.

Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

“…Multilayer Perceptron algorithm has been the best algorithm with the highest success percentage in both of the programs; Decision Trees has been the algorithm which has the lowest success percentage again in both of the programs. …”
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Household overspending model amongst B40, M40 and T20 using classification algorithm by Zulaiha Ali, Othman, Azuraliza, Abu Bakar, Nor Samsiah, Sani, Jamaludin, Sallim

“…The results show that the decision tree through J48 algorithm has produced the easiest rule to be interpreted. …”
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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

“…Hence, a differential search algorithm (DSA) is employed to search for the optimal values of trees and leaves in the RFR algorithm. …”