Search Results - (( model evaluation tree algorithm ) OR ( text classification model algorithm ))

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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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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Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin by Mohd Nordin, Ahmad Nasreen Aqmal

“…The key results encompass dataset preprocessing, Decision Tree classification model training, user interface development, and the evaluation of the Decision Tree model's performance. …”
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Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

Footwear quality evaluation using decision tree and logistic regression models by Tan, Swee Choon

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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 SVGPM performance is compared against current methods in developing a prediction model for IDS. In the third experiment, SVGPM is evaluated on wilt disease data set from remote sensing study, to identify wilt diseased trees in high-resolution image. …”
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Object-based imagery analysis for automatic urban tree species detection using high resolution satellite image by Shojanoori, Razieh

“…In this research, most of satisfactory results achieved from the generic model and proves it can be easily performed to different WorldView-2 images from different areas and provided the high accuracy through algorithms for tree species detection namely, Mesua Ferrea, Samanea Saman, and Casuarina Sumatrana without using any training data. …”
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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…The second experiment introduced a novel dropout regularization technique called multi-channel weighted dropout, designed to enhance model generalization. Comparative evaluations with existing dropout methods demonstrated the superior performance of the proposed technique, particularly when applied within the Algorithm Adaptation framework using DNNs. …”
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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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Water Quality Evaluation and Analysis by Integrating Statistical and Machine Learning Approaches by Amar Lokman, Wan Zakiah Wan Ismail, Nor Azlina Ab Aziz

An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
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The prediction of stock management for Farmasi Chendering by Gamal, Nurul Fatihah

“…This project focuses on Farmasi Chendering, aiming to develop a predictive stock management system using ABC-VEN analysis and the J48 decision tree algorithm. The adapted CRISP-DM methodology guided the development process, encompassing data preparation, modeling, evaluation, and deployment. …”
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A conceptual model for the E-commerce application recommendation framework using exploratory search by Mohammed Mahmudur Rahman, Zulkifly Mohd Zaki, Md. Monirul Islam, Najwa Hayaati Mohd Alwi

Flood prediction model for Kuala Terengganu area using predictive analytics by Mohd Zamri, Najwa An-Nisa

“…Three classification algorithms were tested: Decision Tree, Naive Bayes, and Random Forest. …”
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A Stacked Ensemble Deep Learning Approach For Imbalanced Multi-class Water Quality Index Prediction by Wen Yee Wong, Khairunnisa Hasikin, Anis Salwa Mohd Khairuddin, Sarah Abdul Razak, Hanee Farzana Hizaddin, Mohd Istajib Mokhtar, Muhammad Mokhzaini Azizan

Imbalanced multi-class power transformer fault data classification through Edited Nearest Neighbour-Manhattan-Random Forest by R Azmira, Putri Azmira

“…Furthermore, Random Forest is compared to four machine learning algorithms including Support Vector Machine, XGBoost, Convolutional Neural Networks, and Decision Trees. …”
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A stylometry approach for blind linguistic steganalysis model against translation-based steganography by Mohd Lokman, Syiham

“…The proposed stylometry-based blind steganalysis model consists of two stages, which are stylometric feature selection and classification. …”
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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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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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Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study by Mujtaba, Ghulam, Shuib, Liyana, Raj, Ram Gopal, Rajandram, Retnagowri, Shaikh, Khairunisa

“…Finally, classification model performance was evaluated using four performance measures i.e. overall accuracy, macro precision, macro-F-measure, and macro recall. …”
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