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1
Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…In conclusion, it can be inferred from the analysis that the Random Forest model has better predictive performance compared to the rest of the pallet level partition model with a height of 12 cm used in this research. …”
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2
Benchmarking performance of document level classification and topic modeling
Published 2021“…Finally, we trained Multinomial Naïve Bayes, XGBoost, Bagging, and Deep dense neural network. …”
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Article -
3
Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak
Published 2022“…The COVID-19 Basic Reproduction Number, R0 a predictive model is developed using a linear regression classification algorithm to predict the COVID-19 Basic Reproduction Number, Robased on the actual COVID-19 Basic Reproduction Number, R0. …”
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Flood prediction model for Kuala Terengganu area using predictive analytics
Published 2025“…Three classification algorithms were tested: Decision Tree, Naive Bayes, and Random Forest. …”
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Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…Several studies developed BrC detection and classification models using Hp images. However, the existing models required high computational resources, long training time, and their performance is compromised due to a higher misclassification rate. …”
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6
Multitasking deep neural network models for Arabic dialect sentiment analysis
Published 2022“…Most of the applied approaches are based on single task learning (STL) using machine learning algorithms, such as Logistic Regression (LR) and Hierarchical Classifier (HC) based on the divide-and-conquer approach. …”
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7
Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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8
Phishing image spam classification research trends: Survey and open issues
Published 2020“…Low-level and image metadata are the most widely used features set. …”
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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
Published 2021“…To identify non-infected and BSR-infected trees, the WEKA tool version 3.8.5 was used for classification. The classifiers evaluated in this study were Nave Bayes (NB), Multilayer Perceptron (MLP), and Random Forest (RF). …”
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10
Machine learning approach of predicting Airline flight delay using Naïve Bayes Algorithm / Ahmad Adib Baihaqi Shukri ... [et al.]
Published 2024“…This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. …”
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Evaluating machine learning algorithms for sentiment analysis: a comparative study to support data-driven decision making
Published 2025“…Upon evaluating the models, the findings reveal notable differences in accuracy. …”
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Article -
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Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri
Published 2024“…This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. …”
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13
Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation
Published 2013“…Reflectance spectra were pre-processed and principal component analysis (PCA) was performed to obtain PC scores as input features used in different pattern recognition algorithms in order to select the best learning model of Ganoderma discrimination. …”
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Sentiment analysis of domestic violence prediction using Naive Bayes algorithm / Nurulizzah Mohd Rahiman
Published 2024“…The research objectives focus on studying and applying the Naive Bayes algorithm for sentiment analysis on tweets related to domestic violence, aiming to provide insights for researchers, government agencies, policymakers, and the public and develop a prediction model using Naive Bayes algorithm to evaluate its performance. …”
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Prediction of UiTM student academic performance using Naive Bayes algorithm / Muhammad Irfan Zahin Jailani
Published 2024“…With the help of customized interventions and early identification of at-risk pupils, the proposed approach seeks to increase graduation rates and overall achievement.The main objectives of this study include studying the Naive Bayes algorithm in student academic performance prediction, designing and developing a student academic performance prediction model utilizing Naive Bayes, and evaluating the accuracy of the prediction prototype using the developed model. …”
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Sentiment analysis on airline reviews using Naive Bayes / Nurul Sarah Aliessa Che Harun
Published 2025“…In the design and implementation phases, TF-IDF was considered in cleaning and preparing the reviews for application, while the construction of a sentiment analysis model was implemented through the use of the Multinomial Naive Bayes algorithm. …”
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Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali
Published 2025“…This study explores the application of sentiment analysis using the Naive Bayes algorithm to understand public perceptions of marital issues, particularly factors contributing to the rising divorce rate. …”
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Sentiment Analysis of Airline Reviews Using Naive Bayes Algorithm / Ahmad Firdaus Maliki
Published 2021“…The overview for the methodology is divided into three phases which are preliminary phase, design and implementation phase and evaluation phase. Several classifier models have been built by using Naive Bayes algorithm during the design and implementation phase where the model that has the highest accuracy has been chosen for this project. …”
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A behavioral trust model for internet of healthcare things using an improved FP-growth algorithm and Naïve Bayes classifier
Published 2021“…To ensure security, the threats can largely be tackled by employing a Trust Management Model (TMM) which will critically evaluate the behavior or activity pattern of the nodes and block the untrusted ones. …”
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