Search Results - optimal bayes algorithm*

Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…Consequently, during peak hours, finding a vacant parking bay is more of a difficult task. This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Random Forest and Extreme Gradient Boosting with Bayesian Hyperparameter Optimization for Landslide Susceptibility Mapping in Penang Island, Malaysia by Dorothy, Martin Atok, Soo See, Chai, Kok Luong, Goh, Neha, Gautam, Kim On, Chin

“…This research focuses on improving the predictive capabilities of the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms by applying Bayesian Hyperparameter Optimization (BayesOpt). …”
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Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging by Olanrewaju, Rashidah Funke, Al-Qudah, Dua'a Mahmoud Mohammad, Azman, Amelia Wong, Yaacob, Mashkuri

“…However, their performances are not well optimized. This work proposes a hybrid method that optimize cache replacement algorithm using Naïve Bayes (NB) based approach. …”
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Utilize Medical Text Data to Estimate Disease Types by Using Naïve Bayes and ANN Classifier by Mujiono, Sadikin, Deshinta, Arrova Dewi, Purwanto S., Katijan, Ibrohim, Thohari

“…The combination of its representation results with the structured format data is then used as the dataset to build the model for disease type prediction based on Naïve Bayes and Artificial Neural Network classifier. By using these two algorithms, the results of the classification of the kind of disease. …”
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Comparison of hidden Markov Model and Naïve Bayes algorithms among events in smart home environment by Babakura, Abba, Sulaiman, Md Nasir, Mustapha, Norwati, Kasmiran, Khairul A.

“…In this paper, we propose Hidden Markov Model (HMM) and Naïve Bayes (NB) to test the accuracy and response time of the home data and to compare between the two algorithms. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…In its operation, the metaheuristic algorithm optimizes the feature selection process,which will later be processed using the classification algorithm.Three (3) meta-heuristics were implemented, namely Genetic Algorithm, Particle Swarm Optimization, and Cuckoo Search Algorithm; the experiment was conducted, and the results were collected and analyzed. …”
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Classification of Diabetes Mellitus using Ensemble Algorithms by Noor, N.A.B.S., Elamvazuthi, I., Yahya, N.

“…The objective of this study is to perform DM classification using various machine learning algorithms. In this paper, individual classifiers such as Support Vector Machine, Naïve Bayes, Bayes Net, Decision Stump, k - Nearest Neighbors, Logistic Regression, Multilayer Perceptron and Decision Tree are experimented. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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Predicting factors of library traffic for UiTMCTKKT Cendekiawan Library using predictive analytics / Azzatul Husna Abdul Aziz by Abdul Aziz, Azzatul Husna

“…The CRISP-DM methodology was followed to apply machine learning algorithms, namely Random Forest, Decision Tree, and Naive Bayes, to the data gathered in the library which is traffic, book rentals, and questionnaires. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Hui, Bian, Chiew, Kang Leng

“…This study investigates the performance of various conventional machine learning algorithms, including decision trees, naive Bayes, naive Bayes trees, random forest, random trees, MLP, and SVM, in detecting network intrusions using binary and multi-classification approaches. …”
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Feature selection based on particle swarm optimization algorithm for sentiment analysis classification by Nurcahyawati, Vivine, Mustaffa, Zuriani

“…An improved approach was proposed to increase the sentiment analysis accuracy based on text pre-processing and Naïve Bayes Classifier algorithm hybrid with Particle Swarm Optimization (NBC-PSO). …”
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A malicious URLs detection system using optimization and machine learning classifiers by Lee, Ong Vienna, Heryanto, Ahmad, Mohd Faizal, Ab Razak, Anis Farihan, Mat Raffei, Eh Phon, Danakorn Nincarean, Shahreen, Kasim, Sutikno, Tole

“…Based on this combination as well as significant features, this paper shows promising results with higher detection accuracy. The bio-inspired algorithm: particle swarm optimization (PSO) is used to optimized URLs features. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs by Aljanabi, Mohammad, Mohd Arfian, Ismail, Ali, Ahmed Hussein

“…However, these algorithms suffer from many lacks especially when apply to detect new type of attacks, and need for new algorithms such as JAYA algorithm, teaching learning-based optimization algorithm (TLBO) algorithm is arise. …”
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Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection by Siti, Mujilahwati, Noor Zuraidin, Mohd Safar, Ku Muhammad Naim, Ku Khalif, Nasyitah, Ghazalli

“…This study examines the optimization of Indonesian text sentiment analysis through the integration of feature selection using a genetic algorithm (GA) with deep learning models. …”
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New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

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Prediction of Heart Disease Risk Using Machine Learning with Correlation-based Feature Selection and Optimization Techniques by Reddy, K.V.V., Elamvazuthi, I., Aziz, A.A., Paramasivam, S., Chua, H.N., Pranavanand, S.

“…The Optimizable k-Nearest Neighbors algorithm achieved an utmost accuracy of 95.04, area under the ROC curve of 0.99 on the Correlation-based Feature Selection optimal set, and that of 90.34, 0.96 respectively, on full features. …”
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Discovering optimal features using static analysis and a genetic search based method for Android malware detection by Ahmad Firdaus, Zainal Abidin, Nor Badrul, Anuar, Ahmad, Karim, Mohd Faizal, Ab Razak

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Balancing data utility versus information loss in data-privacy protection using k-Anonymity by Esmeel, Thamer Khalil, Hasan, Md Munirul, Kabir, Muhammad Nomani, Ahmad, Firdaus

“…Based on the classification accuracy, the optimal values of k and c are obtained, and thus, the optimal k and c can be used for kanonymity algorithm to anonymize optimal number of columns of the dataset.…”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning by Muhammad Ruhul Amin, Shourov, Husman, Muhammad Afif, Toha, Siti Fauziah, Jasni, Farahiyah

“…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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