Search Results - (( model evaluation tree algorithm ) OR ( using optimization method algorithm ))*

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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Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree by Arowolo, Micheal Olaolu, Adebiyi, Marion Olubunmi, Adebiyi, Ayodele Ariyo

“…The performances of the model are evaluated and validated using the classification accuracy to compare existing approaches in the literature. …”
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Classification of Google Play application using decision tree algorithm on sentiment analysis of text reviews / Aqil Khairy Hamsani, Ummu Fatihah Mohd Bahrin and Wan Dorishah Wan A... by Hamsani, Aqil Khairy, Mohd Bahrin, Ummu Fatihah, Wan Abdul Manan, Wan Dorishah

“…The project's objectives are to study the classifying approach of Google Play Store application reviews using the Decision Tree algorithm, develop a prototype of a classifying application program, and evaluate the accuracy model of the review classification program. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. Numerous researchers have tried different methods to enhance the algorithm to improve performance, some of these methods include Support Vector Machine (SVM), Decision Trees, Extreme Learning Machine (ELM), Kernel Extreme Learning Machine (KELM), and Deng’s Reduced Kernel Extreme Learning Machine (RKELM). …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

“…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Decision tree optimization for sukuk rating prediction by Kartiwi, Mira, Gunawan, Teddy Surya, Arundina, Tika, Omar, Mohd. Azmi

“…The results indicate that the decision tree model with Gini index as the criterion performs significantly better than the model produced using decision tree algorithm.…”
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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

“…The optimized LightGBM model was trained and evaluated using metrics such as accuracy, precision, and AUC-ROC on the test set, with cross-validation to ensure robustness and generalizability. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…Using the NSL-KDD dataset for evaluation, the proposed method demonstrates superior performance compared to conventional algorithms and related deep learning techniques, achieving higher precision, recall, F1 scores and overall accuracy in both binary and multi-class classification tasks. …”
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Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor by Mohamad Nor, Ahmad Azhari

“…Subsequently, predictive models employing k-nearest neighbour and decision tree algorithms are constructed and evaluated based on accuracy, precision, and recall metrics. …”
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Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem by Wong, Jerng Foong

“…Multidimensional Knapsack Problem (MKP) has been widely used to model real-life combinatorial problems. It is also used extensively in experiments to test the performances of metaheuristic algorithms and their hybrids. …”
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Electricity distribution network for low and medium voltages based on evolutionary approach optimization by Hasan, Ihsan Jabbar

“…This thesis proposes an algorithm to find the optimum distribution substation placement and sizing by utilizing the PSO algorithm and optimum feeder routing using modified Minimum Spanning Tree (MST). …”
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Applications of Data-driven Models for Daily Discharge Estimation Based on Different Input Combinations by Kumar M., Elbeltagi A., Pande C.B., Ahmed A.N., Chow M.F., Pham Q.B., Kumari A., Kumar D.

Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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Industrial implementation of machine learning forecasting algorithms for large-scale Solar Heat for Industrial Process (SHIP) Systems by Manu, Abdurrahman, Haja Mohideen, Ahmad Jazlan, Akhter, Muhammad Naveed, Ahmad Huzri, Muhammad Danial, Mohd Ibrahim, Azhar, Mohd Zaki, Hasan Firdaus, Sreeram, Victor

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A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

“…By evaluating the model on food dataset FOOD101, extracting of features take 80.23 seconds and classifying and training of incremental algorithm take 1253.36 seconds with 77.72% test accuracy. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Near-infrared spectroscopy modeling of combustion characteristics in chip and ground biomass from fast-growing trees and agricultural residue by Shrestha, Bijendra, Posom, Jetsada, Pornchaloempong, Pimpen, Sirisomboon, Panmanas, Shrestha, Bim Prasad, Ariffin, Hidayah

“…The optimal model was selected by evaluating the coefficients of determination in the prediction set (R2P), root mean square error of prediction (RMSEP), and RPD values. …”
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Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary by Mohd Zamary, Nurul Aida

“…The project successfully achieved its objectives by analyzing the literature, developing the decision tree algorithm, and evaluating the accuracy of the model. …”
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Optimized Decision Forest for Website Phishing Detection by Balogun, A.O., Mojeed, H.A., Adewole, K.S., Akintola, A.G., Salihu, S.A., Bajeh, A.O., Jimoh, R.G.

“…Nonetheless, given the dynamism of phishing efforts, there is a constant requirement for novel and efficient website phishing detection solutions. In this study, an optimized decision forest (ODF) method for detecting website phishing is proposed ODF involves the use of a genetic algorithm (GA) for the selection of optimal diverse individual trees in a forest to generate an efficient sub-forest. …”
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