Search Results - (( model evaluation _ algorithm ) OR ( bayes classification based algorithm ))

Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri by Shukri, Ahmad Adib Baihaqi

“…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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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad by Ahmad, Nurul Atirah

“…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 by Mohammed Nadir bin Ali

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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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... by Ahmad, Nurul Atirah, Abu Samah, Khyrina Airin Fariza, Ahmad Kushairi, Nuwairah Aimi

“…This project implements the Naive Bayes algorithm as the classification algorithm. …”
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An Automated System For Classifying Conference Papers by Ngan, Seon Choon Han

“…The project is also aimed to select the best classification model for the system, based on an empirical study. …”
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Data mining techniques for disease risk prediction model: A systematic literature review by Ahmad W.M.T.W., Ghani N.L.A., Drus S.M.

“…Decision making; Decision trees; Forecasting; Health care; Soft computing; Accuracy evaluation; Classification technique; Data mining algorithm; Descriptive analysis; Disease risks; Infectious disease; Risk prediction models; Systematic literature review; Data mining…”

Sentiment analysis for online fashion clothing review using Support Vector Machine (SVM) algorithm / Muhammad Hakam Musawi Mohd Hamdi by Mohd Hamdi, Muhammad Hakam Musawi

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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…Using the NSL-KDD dataset for evaluation, the proposed method demonstrates superior performance compared to conventional algorithms and related deep learning techniques, achieving higher precision, recall, F1 scores and overall accuracy in both binary and multi-class classification tasks. …”
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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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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. The application of GA for data dimensionality reduction from 41,140 to 20,769 features, coupled with fitness evaluation based on SVM, resulted in an observed increase in accuracy by 8.10% for SVM, 36.1% for Naïve Bayes, 7.82% for LSTM, 5.47% for DNN, and 6.25% for CNN. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…Furthermore, the efficacy of different models based on heuristic hyperparameter tuning is evaluated in which the different kernel function for Support Vector Machine, various distance metrics of k-Nearest Neighbors. …”
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An enhanced gated recurrent unit with auto-encoder for solving text classification problems by Zulqarnain, Muhammad

“…Based on various types of performance evaluation parameters, a considerable amount of improvement has been observed in the performance of the proposed model as compared to other standard classification techniques, and showed better effectiveness and efficiency of the developed model.…”
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Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

“…The existing approaches are based on traditional machine learning algorithms, such as support vector machine (SVM). …”
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Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

“…The proposed EBrC-Net model is based on deep learning (DL) based approach. …”
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A COMPARATIVE STUDY OF MACHINE LEARNING MODELS FOR PREDICTION OF AUTISM SPECTRUM DISORDER USING SCREENING DATA by Yeap, Ming Yue

“…The performance of the classification models for ASD will be compared. Finally, the best classification model for ASD prediction was a model trained using the Support Vector Machine (SVM) algorithm…”
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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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An efficient computational intelligence technique for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Samir, B.B.

“…The technique has considered the occurrence frequency of each amino acid in a sequence. Popular classification algorithms such as decision tree, naive Bayes, neural network, random forest and support vector machine have been employed to evaluate the effectiveness of the encoding method utilized in the proposed framework. …”
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Benchmarking performance of document level classification and topic modeling by Bhatti, Muhammad Shahid, Ullah, Azmat, Latip, Rohaya, Sohail, Abid, Riaz, Anum, Hassan, Rohail

“…State-of-the-art machine learning and deep dense neural network approaches for Urdu news classification have been used. Finally, we trained Multinomial Naïve Bayes, XGBoost, Bagging, and Deep dense neural network. …”
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A stylometry approach for blind linguistic steganalysis model against translation-based steganography by Mohd Lokman, Syiham

“…The performance of the stylometry-based blind steganalysis model is then evaluated based on all false rate, missing rate and accuracy rate and compared against three other standard classifiers in steganalysis; Naive Bayes (NB), k-Nearest Neighbor (k-NN), and Decision Tree (J48). …”
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