Search Results - (( model evaluation bayes algorithm ) OR ( pattern classification using algorithm ))
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Data mining techniques for disease risk prediction model: A systematic literature review
Published 2023Conference Paper -
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…This integration optimizes feature extraction by capturing both spatial and temporal relationships, enhancing the detection of complex network behaviors. 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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Thesis -
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The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN
Published 2021“…It was shown that the ensemble-based random subspace k-NN approach achieved the superior classification accuracy (CA) of 99.21%, 93.19%, 93.57% and 90.32% for data-1, data-2, data-3 and data-4, respectively against other models evaluated, namely linear discriminant analysis, support vector machine, random forest, Naïve Bayes and the conventional k-NN. …”
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Article -
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Flood prediction model for Kuala Terengganu area using predictive analytics
Published 2025“…Evaluation using a confusion matrix demonstrated that the Random Forest algorithm achieved the highest performance with accuracy of 98.04%. …”
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Student Project -
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Sentiment analysis of customer review for Tina Arena Beauty
Published 2025“…Future work may involve expanding the dataset, integrating real-time feedback systems, and evaluating advanced algorithms to improve classification performance further. …”
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Student Project -
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Machine learning approach of predicting Airline flight delay using Naïve Bayes Algorithm / Ahmad Adib Baihaqi Shukri ... [et al.]
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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Evaluating machine learning algorithms for sentiment analysis: a comparative study to support data-driven decision making
Published 2025“…Upon evaluating the models, the findings reveal notable differences in accuracy. …”
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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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Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation
Published 2013“…Reflectance spectra were pre-processed and principal component analysis (PCA) was performed to obtain PC scores as input features used in different pattern recognition algorithms in order to select the best learning model of Ganoderma discrimination. …”
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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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Prediction of UiTM student academic performance using Naive Bayes algorithm / Muhammad Irfan Zahin Jailani
Published 2024“…With the help of customized interventions and early identification of at-risk pupils, the proposed approach seeks to increase graduation rates and overall achievement.The main objectives of this study include studying the Naive Bayes algorithm in student academic performance prediction, designing and developing a student academic performance prediction model utilizing Naive Bayes, and evaluating the accuracy of the prediction prototype using the developed model. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…There are a lot of feature extraction methods and classification methods for iris classification. Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
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Monograph -
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Sentiment analysis on airline reviews using Naive Bayes / Nurul Sarah Aliessa Che Harun
Published 2025“…In the design and implementation phases, TF-IDF was considered in cleaning and preparing the reviews for application, while the construction of a sentiment analysis model was implemented through the use of the Multinomial Naive Bayes algorithm. …”
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Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali
Published 2025“…This study explores the application of sentiment analysis using the Naive Bayes algorithm to understand public perceptions of marital issues, particularly factors contributing to the rising divorce rate. …”
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Pattern Recognition for Human Diseases Classification in Spectral Analysis
Published 2022“…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition
Published 2016“…While the algorithm helped to classify different types of wavelengths produced from the sensor, a classification-based algorithm via Pattern Recognition Method will be used to classify and match the food components. …”
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Conference or Workshop Item -
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Songket pattern classification using backpropagation neural network / Nik Aidil Syawalni Nik Mazlan
Published 2024“…Despite to the several system limitations, the project on classifies Songket pattern using BPNN is consider successful. The outcomes of this investigation show the originality and efficacy of employing BPNNs for Songket pattern classification, resulting in good accuracy rates in the classification of Songket. …”
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