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Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms by Nurellezia, Suleiman

“…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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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…Enhancements in cognitive neuroscience and brain imaging technologies such as Human-Computer Interaction (HCI) have started to provide human with the ability to interact directly with the brain. …”
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Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor by Terence Jerome Daim

“…Seven classification algorithms (K-Nearest Neighbour, Logistic Regression, Naive Bayes, Gradient Boosting, AdaBoost, Bagging, and Linear Discriminant Analysis) were meticulously explored for hand gesture recognition. …”
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Customer sentiment analysis through social media feedback: A case study on telecommunication company by Mat Zain, Siti Nur Syamimi, Ramli, Nor Azuana, Adnan, Rose Adzreen

“…The data were then split into training and testing to be tested on the three different supervised learning algorithms used in this study which are Support Vector Machine, Random Forest, and Naïve Bayes. …”
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A COMPARATIVE STUDY OF MACHINE LEARNING MODELS FOR PREDICTION OF AUTISM SPECTRUM DISORDER USING SCREENING DATA by Yeap, Ming Yue

“…This project aims to predict ASD traits in adults based on screening data using a machine learning approach. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Predictive analytics for the sentiment of malaysian place of interest using machine learning models by Qiryn Adriana, Kharul Zaman

“…The data was then divided into training and testing sets, and was trained using three different supervised learning algorithms, namely Support Vector Machine, Random Forest, and Naive Bayes. …”
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Customer sentiment analysis through social media feedback by Siti Nur Syamimi, Mat Zain

“…The data were then split into training and testing to be tested on the three different supervised learning algorithms used in this study which are Support Vector Machine, Random Forest, and Naïve Bayes. …”
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