Search Results - (( developing effective bayes algorithm ) OR ( java application tree algorithm ))
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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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Sentiment analysis regarding childcare issues using Naive Bayes Algorithm / Alis Farhana Zulkipeli
Published 2025“…This study applies the Naive Bayes algorithm for sentiment analysis to assess public perceptions of childcare issues, particularly child abandonment and accidents. …”
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak
Published 2021“…A classifier model is developed using Naive Bayes characteristics. A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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Comparison of hidden Markov Model and Naïve Bayes algorithms among events in smart home environment
Published 2014“…In this paper, we propose Hidden Markov Model (HMM) and Naïve Bayes (NB) to test the accuracy and response time of the home data and to compare between the two algorithms. …”
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Machine Learning Applications in Offense Type and Incidence Prediction
Published 2024“…Naive Bayes, a probabilistic classifier based on Bayes' theorem, is particularly effective in handling large datasets and making accurate predictions. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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A comparative study in classification techniques for unsupervised record linkage model
Published 2011“…A variety of record linkage algorithms with different steps have been developed in order to detect such duplicate records. …”
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Mining Sequential Patterns using I-PrefixSpan
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Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary
Published 2024“…This project aims to develop a decision-making support model for diabetes diagnosis and treatment recommendation using the decision tree algorithm. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Advanced data mining techniques for landslide susceptibility mapping
Published 2021“…The investigation was carried out to ascertain the effectiveness of Naïve Bayes Multinomial (NBM) and Random Trees (RT) in landslide susceptibility mapping. …”
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Analyzing customer reviews for ARBA Travel using sentiment analysis
Published 2025“…Among these, Naive Bayes achieved the highest performance with an accuracy of 93.67% and an F1-score of 93.54%, making it the most effective model for sentiment classification in this context. …”
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Evaluating Machine Learning Algorithms for Fake Currency Detection
Published 2024“…In this study, we evaluate the effectiveness of six supervised machine learning algorithms—K-Nearest Neighbor, Decision Trees, Support Vector Machine, Random Forests, Logistic Regression, and Naive Bayes—in detecting the authenticity of banknotes. …”
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A comparative analysis of machine learning algorithms for diabetes prediction
Published 2024“…This study focuses on comparing the performance of three machine learning algorithms, namely Naive Bayes (NB), Support Vector Machines (SVM), and Random Forest (RF), in predicting diabetes using two datasets: Pima Indians Diabetes Dataset (PIDD) and the Diabetes 2019 Dataset (DD2019), and the need to identify the most accurate and effective algorithm for diabetes prediction. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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Making programmer effective for software development teams: An extended study
Published 2017“…In order to find the possible combination of personality types between team-leader and programmer, this study applied Genetic Algorithm (GA) and Johnson's Algorithm (JA) on data. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu
Published 2014“…Multilayer Perceptron algorithm has been the best algorithm with the highest success percentage in both of the programs; Decision Trees has been the algorithm which has the lowest success percentage again in both of the programs. …”
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