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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
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Thesis -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
Published 2012“…The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. …”
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4
Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…The features extracted of time domain and frequency domain in vibration and acoustic will use as database of a Support Vector Machine (SVM) algorithms by using MATLAB R2021a. The result from the SVM algorithms will be used as database for the machine learning in Microsoft Azure. …”
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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024Conference Paper -
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Object-Oriented Programming semantics representation utilizing agents
Published 2011“…Generally, these source codes go through the preprocessing, comparison, extraction, generate program semantics and classification processes. A formal algorithm that can be applied to any two related Java-based source codes examples is invented to generate the semantics of these source codes. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The results reveal that the proposed hybrid algorithm is capable of achieving classification accuracy values of (95.82 % and 97.68 %), detection rates values of (95.8 % and 99.3 %) and false alarm rates values of (0.083 % and 0.045 %) on both KDD CUP 99 and NSL KDD. …”
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Predictive Modelling of Stroke Occurrence among Patients using Machine Learning
Published 2023“…Variables such as age, gender, hypertension, diabetes, smoking status, BMI, and medical history were considered. Advanced machine learning algorithms, including logistic regression, decision trees, random forests, and support vector machines, were utilized to analyses the dataset and develop a predictive model. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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11
Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables
Published 2025“…This study developed fine-scale predictive models using machine learning algorithms; Artificial Neural Networks (ANN), Random Forest (RF), and Support Vector Machines (SVM) to estimate mosquito abundance and dengue risk at the species level based on daily microclimatic data (temperature, relative humidity, and rainfall) collected over 26 weeks in Kuala Selangor, Malaysia. …”
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Reliability fuzzy clustering algorithm for wellness of elderly people
Published 2019“…By gleaning insights from the data, the fuzzy clustering can learn from data, identify patterns and make decisions with minimal human intervention. …”
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Conference or Workshop Item -
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…Our study introduces a new model for predicting reservoir water levels. An extreme learning machine, the multi-kernel least square support vector machine model (MKLSSVM), is developed to predict the water level of a reservoir in Malaysia. …”
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Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali
Published 2025“…These insights can assist policymakers, mental health professionals, and marriage counselors in developing targeted interventions to support healthier relationships and strengthen societal well-being.…”
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Automated Nutritional Guidance for Obesity Management: Insights from Machine Learning, Naïve Bayes, Random Forest
Published 2025“…The system utilizes a combination of machine learning algorithms, nutritional databases, and user input to provide personalized dietary plans aligned with individual health goals, dietary preferences, and lifestyle patterns. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…Future work should be focusing on data collection of the E-Nose sensors and the improvement of the learning algorithm robustness towards environmental noise during data acquisition, such as evaporation and contamination of odor samples.…”
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Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection
Published 2024“…The proposed model leverages machine learning algorithms for autonomous detection of insulators. …”
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Deep learning in public health: Comparative predictive models for COVID-19 case forecasting
Published 2024“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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Assessment of crops healthiness via deep learning approach: Python / Mohamad Amirul Asyraf Mohd Ramli
Published 2023“…By leveraging image processing techniques, statistical analysis and machine learning algorithms, Python enables the extraction of relevant features and patterns from data. …”
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Student Project -
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Improve of contrast-distorted image quality assessment based on convolutional neural networks
Published 2023“…Many image quality assessment algorithms (IQAs) have been developed during the past decade. …”
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