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Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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Final Year Project -
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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Final Year Project -
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Entiment analysis of public perception on AI chatbots using Support Vector Machine (SVM) algoritm / Tuan Nur Azlina Tuan Ibrahim
Published 2024“…Facing challenges with existing methods, the Support Vector Machine (SVM) algorithm is employed for its proficiency in handling textual data. …”
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Thesis -
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…The supervised machine learning algorithm, SVM and Decision Tree are used for the estimation of the mangrove age into young and mature. …”
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Thesis -
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Improving Support Vector Machine Performance using Modified Similarity Distance Plotting-Data Reduction
Published 2025“…The Support Vector Machine (SVM) is well-regarded for its high classification accuracy, but its computational efficiency is often challenged by large datasets. …”
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Mixed variable ant colony optimization technique for feature subset selection and model selection
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Conference or Workshop Item -
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Support vector machine in precision agriculture: a review
Published 2021“…The applications of SVM in precision agriculture (PA) are compared by identifying its interactions with variables, comparing its model performance, highlighting its strengths and weaknesses, as well as suggestions for improvements. …”
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Gender identification using support vector machines
Published 2023“…This thesis is introduces SVM theory application and its algorithmic implementations.…”
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Analysing machine learning models to detect disaster events using social media
Published 2023text::Thesis -
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Age prediction on face features via multiple classifiers
Published 2018“…We were able to recognize that the accuracy of SVR algorithm is better than the accuracy of KNN and SVM classifiers.…”
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Classification of basal stem rot disease in oil palm using dielectric spectroscopy
Published 2018“…For feature selection algorithms, SVM-FS model gave the best classification accuracies compared to GA and RF; ranged from 81.82% to 88.64% with SVM and kNN as the best classifiers. …”
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Thesis -
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A comparative analysis of LSTM, SVM, and GSTANN models for enhancing solar power prediction
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Proceeding Paper -
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Multilingual Sentiment Analysis From Students Feedback: Optimal Techniques And Resources For Bengali Lingual Data
Published 2024thesis::doctoral thesis -
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Classification of Citrus (Rutaceae) by Using Image Processing
Published 2019“…A machine learning algorithms, SVM have been used to build species identification models. …”
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Undergraduate Final Project Report -
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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination
Published 2025“…Among these, the SVM model showed the best predictive accuracy, R2 of 0.98, with the lowest AIC (56.75), RMSE (1.50), and MAE (1.22) values, highlighting its robustness in capturing the intricate dependencies between operational parameters and removal performance. …”
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Article -
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A Proposed False Report Identification Algorithm for a Mobile Application in the IoT Environment
Published 2024Proceedings Paper -
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Evaluating JA-ABC5 hyperparameter optimisation with classifiers
Published 2024“…However, its application in hyperparameter optimisation for machine learning classifiers deserves exploration.The effectiveness of ABC and its modified version, JA-ABC5, for hyperparameter optimisation across various classifiers, including Support Vector Machine (SVM) and K-Nearest Neighbour (KNN), is studied in this research. …”
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Conference or Workshop Item
