Search Results - (( developing theme classification algorithm ) OR ( java classification system algorithm ))
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Classification System for Heart Disease Using Bayesian Classifier
Published 2007“…In this system a Bayesian algorithm was used in order to implement the system. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
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Undergraduates Project Papers -
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…So, the integration of Artificial Neural Network (ANN) with an Expert System for material classification was explored. The computational tool, Matlab was proposed for classification with Levenberg-Marquardt training algorithm, which provided faster rate of convergence for feed forward network. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The results reveal that the proposed hybrid algorithm is capable of achieving classification accuracy values of (95.82 % and 97.68 %), detection rates values of (95.8 % and 99.3 %) and false alarm rates values of (0.083 % and 0.045 %) on both KDD CUP 99 and NSL KDD. …”
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Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
Published 2012“…The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. …”
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Classification for Quran authentication using characters and diacritics hashed values
Published 2024journal::journal article -
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…To evaluate this technique, an experiment was conducted on two geospatial systems developed using Java programming language where the Chidamber and Kemerer (CK) metrics were used. …”
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Evaluating the usability of a Quranic theme extraction and visualization system using task-based usability testing
Published 2025“…This study presents a task-based usability evaluation of a Quranic Theme Extraction and Visualization System, which integrates Natural Language Processing (NLP) techniques which are RAKE algorithm for keyword extraction and DistilBERT for theme classification. …”
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Object-Oriented Programming semantics representation utilizing agents
Published 2011“…Generally, these source codes go through the preprocessing, comparison, extraction, generate program semantics and classification processes. A formal algorithm that can be applied to any two related Java-based source codes examples is invented to generate the semantics of these source codes. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…The features extracted of time domain and frequency domain in vibration and acoustic will use as database of a Support Vector Machine (SVM) algorithms by using MATLAB R2021a. The result from the SVM algorithms will be used as database for the machine learning in Microsoft Azure. …”
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Monograph -
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…Samples data were recorded in the morning before food intake and two hours after food intake using four MQ 2, MQ 5, MQ 6 and MQ 8 sensors, in previously built Electronic Nose prototype system. A 5-fold cross-validation testing was implemented for classification results analysis. …”
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Prediction of breast cancer diagnosis using machine learning in Malaysian women
Published 2024“…The three frequently used ML algorithms were deep learning, support vector machine (SVM), and cluster analysis. …”
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Identification of Quran recitation segment from speech video recording / Liliana Nulkasim @ Mohd Kassim
Published 2017“…A random forest classifier algorithm is employed in Spyder IDE using python language as a machine learning language for predict the type of an audio. …”
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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. The results were visualized using an interactive dashboard developed in Power BI, allowing users to explore sentiment trends, keyword frequency, and review distributions by gender, platform, and time. …”
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