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Evaluation of fall detection classification approaches
Published 2012“…The algorithms are Multilayer Perceptron, Naive Bayes, Decision tree, Support Vector Machine, ZeroR and OneR. …”
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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad
Published 2023“…This project implements the Naive Bayes algorithm as the classification algorithm. …”
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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad, Khyrina Airin Fariza Abu Samah and Nuwairah Aimi Ahmad...
Published 2023“…This project implements the Naive Bayes algorithm as the classification algorithm. …”
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A New Model For Network-Based Intrusion Prevention System Inspired By Apoptosis
Published 2024thesis::doctoral thesis -
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Comparative analysis for topic classification in juz Al-Baqarah
Published 2018“…The SVM performance is then compared against other classification algorithms such as Naive Bayes, J48 Decision Tree and K-Nearest Neighbours. …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The BayesNet ML-ADR classifier model performance evaluation with the highest kappa statistic value of 0.991, the lowest mean absolute error value of 0.0009, weighted average precision values of 99.2 %, ROC area coverage of 100 %, the most down trip decision time of 10 ms better than the existing 20 ms for conventional ADR. …”
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Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor
Published 2023“…The evaluation, based on macro F1 scores to balance precision and recall, aimed to assess their effectiveness. …”
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Machine learning–based fault detection for condition monitoring of a three-phase induction motor using current signature
Published 2026“…Different classification techniques such as Support Vector Machines-SVM, k- nearest Neighbor-KNN, Ensemble, Decision Tree, Linear discriminant, and Nave Bayes are applied on data of stator current to find which algorithm is giving the highest percentage of efficiency. …”
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Spear- phishing attack detection using artificial intelligence
Published 2024“…The system integrates text preprocessing techniques to enhance classification accuracy and was tested with real-world datasets, demonstrating effective spam detection. …”
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Final Year Project / Dissertation / Thesis -
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Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri
Published 2024“…This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. …”
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Sentiment analysis of domestic violence prediction using Naive Bayes algorithm / Nurulizzah Mohd Rahiman
Published 2024“…The research objectives focus on studying and applying the Naive Bayes algorithm for sentiment analysis on tweets related to domestic violence, aiming to provide insights for researchers, government agencies, policymakers, and the public and develop a prediction model using Naive Bayes algorithm to evaluate its performance. …”
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Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim
Published 2024“…The objectives of this project are to study the requirement of the Naive Bayes algorithm in Mobile Banking Trojan detection, to develop a webbased detection system for Mobile Banking Trojan using Naive Bayes, and to evaluate the performance and accuracy of the Naive Bayes algorithm in the Mobile Banking Trojan detection. …”
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An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach
Published 2015“…Therefore, Statisticalbased Packet Header Anomaly Detection (SPHAD) and a hybridized Naive Bayes and Random Forest classifier (NB+RF) are considered for the ADS, and Signature-based Packet Header Intrusion Detection (SPHID) is proposed as the SDS. …”
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An improved hybrid learning approach for better anomaly detection
Published 2011“…Next, a number of classifiers like Naïve Bayes, OneR, and Random Forest separately applied to these data to group all data into the right categories. …”
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Anomaly-based intrusion detection through K-means clustering and naives Bayes classification
Published 2013“…We propose an integrated machine learning algorithm across K-Means clustering and Naïve Bayes Classifier called KMC+NBC to overcome the aforesaid drawbacks. …”
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Conference or Workshop Item -
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Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification
Published 2013“…Regrettably, the foremost challenge of this method is to minimize false alarm while maximizing detection and accuracy rate.We propose an integrated machine learning algorithm across K-Mean s clustering and Naïve Bayes Classifier called KMC+NBC to overcome the aforesaid drawbacks.K-Means clustering is applied to labeling and gathers the entire data into corresponding cluster sets based on the data behavior,i.e.…”
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Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging
Published 2016“…This work proposes a hybrid method that optimize cache replacement algorithm using Naïve Bayes (NB) based approach. Naïve Bayes is an intelligent method that depends on Bayes’ probability theory integrated with Adaptive Weight Ranking Policy (AWRP) via dynamic aging factor to improve the response time and network performance. …”
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