Search Results - (( java application based algorithm ) OR ( pattern classification bayes algorithm ))

Naive Bayes-guided bat algorithm for feature selection by Taha A.M., Mustapha A., Chen S.-D.

“…Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”

Naive bayes-guided bat algorithm for feature selection. by Taha, Ahmed Majid, Mustapha, Aida, Chen, Soong Der

“…Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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Evaluation of fall detection classification approaches by Kerdegari, Hamideh, Samsudin, Khairulmizam, Ramli, Abdul Rahman, Ghotoorlar, Saeid Mokaram

“…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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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms by Azwa, Abdul Aziz, Fadhilah, Ahmad

“…The comparative analysis is also conducted to discover the best classification model for prediction. From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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Android Mobile Malware Classification Based on System Call and Permission Using Tokenization by Intan Nurfarahin Binti Ahmad

Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

“…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
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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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An improved multiple classifier combination scheme for pattern classification by Abdullah,

“…Combining multiple classifiers are considered as a new direction in the pattern recognition to improve classification performance. …”
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Pixel-based feature for android malware family classification using machine learning algorithms by Mohd Zamri, Osman, Rahiwan Nazar, Romli, Ahmad Firdaus, Zainal Abidin, Mohd Faaizie, Darmawan

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Classification Of Hand Movements Based On Discrete Wavelet Transform And Enhanced Feature Extraction by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…The extracted features are then fed into the machine learning algorithm for classification process. Four popular machine learning algorithms include k-nearest neighbor (KNN), linear discriminate analysis (LDA), Naïve Bayes (NB) and support vector machine (SVM) are used in evaluation. …”
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SpickME: Choosing spectacles prediction system by using multinomial Naïve Bayes / Nurul Nabilah Johari by Johari, Nurul Nabilah

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The analysis of road traffic fatality pattern for Selangor, Malaysia case study by Radzuan, N. Q., Mohd Hasnun Ariff, Hassan, Abu Kassim, K. A., Ab. Rashid, A. A., Intan Suhana, Mohd Razelan, Nur Aqilah, Othman

“…Neural network was seen as the best algorithm to classify road traffic fatality occurrence with 97.0% classification accuracy outperform other algorithms. …”
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A review on classifying and prioritizing user review-based software requirements by Salleh, Amran, Said, Mar Yah, Osman, Mohd Hafeez, Hassan, Sa’Adah

“…Furthermore, we identified Naive Bayes, SVM, and Neural Networks algorithms as dependable and suitable for requirement classification and prioritization tasks. …”
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Ant system-based feature set partitioning algorithm for classifier ensemble construction by Abdullah, , Ku-Mahamud, Ku Ruhana

“…Ensemble method is considered as a new direction in pattern classification. Accuracy and diversity in a set of classifiers are two important things to be considered in constructing classifier ensemble.Several approaches have been proposed to construct the classifier ensemble. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…However, these algorithms often fall short in consistently detecting and classifying network intrusions, particularly when distinctions between classes are subtle or when facing evolving attack patterns. …”
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Identification model for hearing loss symptoms using machine learning techniques by Nasiru Garba Noma

“…The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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Early detection of basal stem rot disease (Ganoderma) in oil palms based on hyperspectral reflectance data using pattern recognition algorithms by Liaghat, Shohreh, Ehsani, Reza, Mansor, Shattri, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja, Azam, Siti H. M. N.

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The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN by Rashid, Mamunur, Bari, Bifta Sama, Hasan, Md Jahid, Mohd Azraai, Mohd Razman, Rabiu Muazu, Musa, Ahmad Fakhri, Ab. Nasir, Anwar, P. P. Abdul Majeed

“…In the present investigation, an ensemble learning-based classification algorithm, namely random subspace k-nearest neighbour (k-NN) has been proposed to classify the motor imagery (MI) data. …”
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A Steganalysis Classification Algorithm Based on Distinctive Texture Features by Hammad B.T., Ahmed I.T., Jamil N.

“…Therefore, in this research, we present a steganalysis classification method based on one of the texture features chosen, such as segmentation-based fractal texture analysis (SFTA), local binary pattern (LBP), and gray-level co-occurrence matrix (GLCM). …”