Search Results - (( model evaluation bayes algorithm ) OR ( data classification model algorithm ))

Evaluating machine learning algorithms for sentiment analysis: a comparative study to support data-driven decision making by Mohamad Daud, Nur Hafiza, Shafii, Nor Hayati, Md Nasir, Diana Sirmayunie, Fauzi, Nur Fatihah

“…This research investigates the accuracy and robustness of sentiment analysis models through a comparative analysis of three distinct machine learning algorithms: Bernoulli Naive Bayes, Linear Support Vector Machines, and Logistic Regression. …”
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Machine learning approach of predicting Airline flight delay using Naïve Bayes Algorithm / Ahmad Adib Baihaqi Shukri ... [et al.] by Shukri, Ahmad Adib Baihaqi, Mohamed Yusoff, Syarifah Adilah, Warris, Saiful Nizam, Abu Bakar, Mohd Saifulnizam, Kadar, Rozita

“…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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Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali by Mohd Razali, Farah Nabila

“…The Naive Bayes algorithm was chosen for its efficiency in text classification and ability to handle large volumes of unstructured data. …”
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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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Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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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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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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A New Model For Network-Based Intrusion Prevention System Inspired By Apoptosis by Mohammed Nadir bin Ali

Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary by Mohd Zamary, Nurul Aida

“…The phase of this project is divided into data preprocessing, implementation of the decision tree algorithm, and evaluation of the algorithm and prototype. …”
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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…”

Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…The proposed method managed data and model complexity effectively while maintaining high computational efficiency. …”
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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 Automated System For Classifying Conference Papers by Ngan, Seon Choon Han

“…A randomised stratified 5- fold cross validation was then applied on several data mining algorithms and evaluated using the F-measure as a metric. …”
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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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Flood prediction model for Kuala Terengganu area using predictive analytics by Mohd Zamri, Najwa An-Nisa

“…Three classification algorithms were tested: Decision Tree, Naive Bayes, and Random Forest. …”
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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

“…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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A COMPARATIVE STUDY OF MACHINE LEARNING MODELS FOR PREDICTION OF AUTISM SPECTRUM DISORDER USING SCREENING DATA by Yeap, Ming Yue

“…The steps include domain understanding, data selection, data pre-processing, data transformation, data mining/modelling and model evaluation. …”
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Classification of metamorphic virus using n-grams signatures by A Hamid, Isredza Rahmi, Md Sani, Nur Sakinah, Abdullah, Zubaile, Mohd Foozy, Cik Feresa, Kipli, Kuryati

“…Then, the virus cluster is evaluated using Naïve Bayes algorithm in terms of accuracy using performance metric. …”
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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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Fake news detection: A machine learning approach by Yeoh, Dennis Guan Lee

“…The final model chosen to be deployed was a model trained using a Multinomial Naïve Bayes algorithm.…”
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