Search Results - (( using vectorization learning algorithm ) OR ( automatic classification using algorithm ))
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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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Hybridization Of Optimized Support Vector Machine And Artificial Neural Network For The Diabetic Retinopathy Classification Problem
Published 2019“…Due to the success of many classification problems been proposed with good result, k-Nearest Neighbour, Artificial Neural Network, and Support Vector Machine algorithms are used in this research.…”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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Deep learning metaphor detection with emotion-cognition association
Published 2022“…These well-known ma-chine learning classification algorithms are used at the same time for the purpose of comparison. …”
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Evaluation of fall detection classification approaches
Published 2012“…This paper presents the comparison of different machine learning classification algorithms using Waikato Environment for Knowledge Analysis (WEKA) platform for classifying falling patterns from ADL patterns. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Fuzzy support vector machine based fall detection method for traumatic brain injuries: A new systematic approach of combining fuzzy logic with support vector machine to achieve hig...
Published 2022“…One of the most commonly used algorithms is Support Vector Machine (SVM). …”
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Using SVMs for Classification of Cross-Document Relationships
Published 2013“…In addition, the results obtained using SVMs were also compared with those from the previous literature using boosting classification algorithm. …”
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Improved relative discriminative criterion using rare and informative terms and ringed seal search-support vector machine techniques for text classification
Published 2019“…Additionally, this study also proposes a hybrid algorithm named: Ringed Seal Search-Support Vector Machine (RSS-SVM) to improve the generalization and learning capability of the SVM. …”
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Stage of maturity banana fruit classification using image processing / Nadia Kasim ... [et al.]
Published 2019“…This study attempted to propose a system that uses image processing to detect the maturity stage of banana based on its color and size using Support Vector Machine (SVM) learning algorithm. …”
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Enhanced extreme learning machine for general regression and classification tasks
Published 2020“…To address this issue, a fast adaptive shrinkage/thresholding algorithm ELM (FASTA-ELM) which uses an extension of forward-backward splitting (FBS) to compute the smallest norm of the output weights in ELM is presented. …”
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Improved personalised data modelling using parameter independent fuzzy weighted k-nearest neighbour for spatio/spectro-temporal data
Published 2021“…Upon exploration of the architecture, the weighted k-nearest neighbours algorithm used for the classification module is found to be prone to misclassification as it relies solely on the majority voting rule to determine the class for new data vector. …”
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Consumer acceptance and perceptions of electric vehicles in Malaysia using sentiment analysis
Published 2025“…The dataset is scrapped data collected from comments on YouTube with Term Frequency-Inverse Document Frequency (TF-IDF) as the feature extraction method. The machine learning algorithm, support vector machine (SVM), is then created to automatically identify and classify comments about EV acceptance and perception. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…A novel feature extraction algorithm was developed to extract the feature vectors. …”
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Predictive analytics for the sentiment of malaysian place of interest using machine learning models
Published 2023“…The focus of this study is to conduct Natural Language Processing (NLP) on tweets and make a better classification of sentiment using Malaya. Furthermore, this study also trains three machine learning algorithms to predict the sentiment of textual data. …”
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Undergraduates Project Papers -
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Consumer acceptance and perceptions of electric vehicles in Malaysia using sentiment analysis
Published 2025“…The dataset is scrapped data collected from comments on YouTube with Term Frequency-Inverse Document Frequency (TF-IDF) as the feature extraction method. The machine learning algorithm, support vector machine (SVM), is then created to automatically identify and classify comments about EV acceptance and perception. …”
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Classification Of Gender Using Global Level Features In Fingerprint For Malaysian Population
Published 2016“…For data mining classification part, there are four popular machine learning classifiers used which are Bayesian Net.work (Bayes Net.), Multilayer Perceptron Neural Network (MLPNN), K-Nearest Neighbor (KNN) and Support Vector Machine (SVM). …”
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An enhanced gated recurrent unit with auto-encoder for solving text classification problems
Published 2020“…Gated Recurrent Unit (GRU) is a type of Recurrent Neural Networks (RNNs), and a deep learning algorithm that contains update gate and reset gate. …”
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Decision-Level Fusion Scheme For Nasopharyngeal Carcinoma Identification Using Machine Learning Techniques
Published 2020“…The study aim is to develop and propose a new automatic classification of NPC tumor using machine learning techniques and feature-based decision-level fusion scheme from endoscopic images. …”
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