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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. …”
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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. …”
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Final Year Project -
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An ensemble data summarization approach based on feature transformation to learning relational data
Published 2015“…A better cluster result can also be produced by combining the cluster results generated from the GA based clustering with Feature Selection and Feature Construction algorithms.…”
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Feedforward neural network for solving particular fractional differential equations
Published 2024“…Then, a single hidden layer of FNN based on Chelyshkov polynomials with an extreme learning machine algorithm (SHLFNNCP-ELM) is constructed for solving FDEsC. …”
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Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia
Published 2024“…Finally, the load forecasting model based on LSSVM-IBFOA is constructed using mean absolute percentage error (MAPE) as the objective function. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia
Published 2024“…Finally, the load forecasting model based on LSSVM‑IBFOA is constructed using mean absolute percentage error (MAPE) as the objective function. …”
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Sentiment analysis for airline services on Twitter using deep learning with word embedding / Mawada Mohamed Nour El Daim El Khalifa
Published 2020“…The role of Sentiment Analysis (SA) is to classify people's opinions into different categories, such as positive and negative from text, using existing algorithms. However, existing approaches such as the Bag of Words (BOW) model is frequently used for text classification, where a document is mapped to a feature vector before the construction of the actual model, using machine learning techniques, like Logistical Regression and Support Vector algorithms. …”
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The capabilities of Multiclass Support Vector Machine (MSVM) training algorithms in grading agarwood essential oil
Published 2024“…This paper purposes to proof the capabilities of multiclass support vector machine (MSVM) training algorithms in grading agarwood essential oil. …”
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Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.]
Published 2024“…This study has investigated five commonly used machine learning algorithm to be constructed as potential models for predicting stroke dataset. …”
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Investigation of features for classification RFID reading between two RFID reader in various support vector machine kernel function
Published 2022“…An indoor positioning using RFID technology based on various kernel function of the support vector machine (SVM), and feature extraction are proposed to determine the location of the goods. …”
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Conference or Workshop Item -
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Application of slantlet transform based support vector machine for power quality detection and classification
Published 2015“…This paper proposed to use Slantlet Transform (SLT) with Support Vector Machine (SVM) to detect and localize several PQ disturbance, i.e. voltage sag, voltage swell, oscillatory-transient, odd-harmonics, interruption, voltage sag plus odd-harmonics, voltage swell plus odd-harmonics, voltage sag plus transient and pure sinewave signal were studied. …”
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Application Of Slantlet Transform Based Support Vector Machine For Power Quality Detection And Classification
Published 2015“…The analysis on PQ disturbances signals was performed in two steps, which are extraction of feature disturbance and classification of the disturbance based on its type. To take on the characteristics of PQ signals, feature vector was constructed from the statistical value of the SLT signal coefficient and wavelets entropy at different nodes. …”
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Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…These output data are analysed to present the optimal prediction output of service restoration using Cuckoo Search Spring – Least Square Support Vector Machine (CSS-LSSVM). …”
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Non-fiducial based electrocardiogram biometrics with kernel methods
Published 2017“…At classification level, Gaussian multi-class Support Vector Machine (SVM) with the One-Against-All (OAA) approach is proposed to evaluate verification performance rates of the feature extraction algorithms. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Feature selection methods such as Boruta, Random Forest (RF), Elastic Net (EN), Recursive Feature Elimination (RFE), learning vector quantization (LVQ), Genetic Algorithm (GA), Cluster Dendrogram (CD), Support Vector Machine (SVM) and Logistic Regression (LR) were combined with RF, SVM, LR, and EN classifiers for 30-day mortality prediction. …”
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Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms
Published 2023“…The transformed data is then modelled using machine learning algorithms such as Naïve Bayes classifier and Support Vector Machine to predict the overall sentiment of tweets, in which the finding depicted an overall positive sentiment surrounding the issue. …”
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Final Year Project Report / IMRAD -
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Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The effect of faults and the effectiveness of the fault tolerant algorithm is demonstrated by observing the speed response of the induction machine, which is the strategy adopted by the majority of researchers in this area. …”
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