Search Results - ((((((means algorithm) OR (bayes algorithm))) OR (_ algorithm))) OR (based algorithm))

A Naïve-Bayes classifier for damage detection in engineering materials by Addin, O., Salit, Mohd Sapuan, Mahdi Ahmad Saad, Elsadig, Othman, Mohamed

“…A method for feature subset selection has also been introduced too. The method is based on mean and maximum values of the amplitudes of waves after dividing them into folds then grouping them by a clustering algorithm (e.g. k-means algorithm). …”
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Ant system-based feature set partitioning algorithm for classifier ensemble construction by Abdullah, , Ku-Mahamud, Ku Ruhana

“…In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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A comparative study between deep learning algorithm and bayesian network on Advanced Persistent Threat (APT) attack detection by Ooi, Hui Ni, Ab Rahman, Nurul Hidayah

“…This means that Multilayer Perceptron algorithm can detect APT attack more accurately. …”
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Anomaly-based intrusion detection through K-means clustering and naives Bayes classification by Mohamed Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md. Nasir

“…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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Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification by Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md Nasir

“…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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A comparative study between deep learning algorithm and bayesian network on Advanced Persistent Threat (APT) attack detection by Ooi, Hui Ni, Ab Rahman, Nurul Hidayah

“…This means that Multilayer Perceptron algorithm can detect APT attack more accurately. …”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…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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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…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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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

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Enhanced Flipping Technique to Reduce Variability in Image Steganography by Kamil S., Abdullah S.N.H.S., Hasan M.K., Bohani F.A.

“…Benchmarking; Discrete cosine transforms; Genetic algorithms; Image coding; Image enhancement; Mean square error; Signal to noise ratio; Bayes method; Cover-image; Data hidden; Embedding capacity; Flipping methods; Least significant bits; Medium; Optimisations; Variability; Visual qualities; Steganography…”

Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit by Shah N.N.H., Razak N.N.A., Razak A.A., Abu-Samah A., Suhaimi F.M., Jamaluddin U.

“…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. Ninety-eight ICU patients? …”

Text Categorization Using Naive Bayes Algorithm by Wan Hazimah, Wan Ismail

“…This paper presents text categorization system based on naive Bayes algorithm. This algorithm has long been used for text categorization tasks. …”
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Text categorization using naive bayes algorithm by Wan lsmail @ W. Abdullah, Wan Hazimah, Kamaruddin, Siti Sakira, Sainin, Mohd Shamrie

“…This paper presents text categorization system based on naive Bayes algorithm. This algorithm has long been used for text categorization tasks. …”
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Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri by Shukri, Ahmad Adib Baihaqi

Subjects: “…Evolutionary programming (Computer science). Genetic algorithms…”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

Subjects: “…Algorithms…”
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Machine learning classifications of multiple organ failures in a malaysian intensive care unit by Norliyana, Nor Hisham Shah, Normy Norfiza, Abdul Razak, Athirah, Abdul Razak, Asma’, Abu-Samah, Fatanah, M. Suhaimi, Ummu Kulthum, Jamaludin

“…Several machine learning algorithms which are decision tree, linear discriminant, naïve Bayes, support vector machines, k-nearest neighbor, AdaBoost, and random forest were used for the classification. …”
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Sentiment analysis of domestic violence prediction using Naive Bayes algorithm / Nurulizzah Mohd Rahiman by Mohd Rahiman, Nurulizzah

Subjects: “…Algorithms…”
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Comparison of Naïve bayes classifier with back propagation neural network classifier based on f - folds feature extraction algorithm for ball bearing fault diagnostic system by Osman Mohamed Addin, Addin, Salit, Mohd Sapuan, Othman, Mohamed, Ahmed Ali, Basheer Ahmed

“…This paper is intended to compare the Naïve bayes classifier for ball bearing fault diagnostic system with the back propagation neural network based on the f-folds feature extraction algorithm. …”
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Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules by Wiliani, Ninuk

“…The accuracy value shows that the KNN algorithm is better when compared to the Naïve Bayes algorithm. …”
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Towards a better feature subset selection approach by Shiba, Omar A. A.

“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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