Search Results - (( java implementation learning algorithm ) OR ( factor affecting selection algorithm ))
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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2
An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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5
Comparing the performance of FCBF, Chi-Square and relief-F filter feature selection algorithms in educational data mining
Published 2019“…There are many feature selection algorithms, however three filter feature selection algorithms FCBF, Chi-Square, and ReliefF are selected due their better performance, and applied on three different studentâ��s data sets. …”
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Comparing the performance of FCBF, Chi-Square and relief-F filter feature selection algorithms in educational data mining
Published 2019“…There are many feature selection algorithms, however three filter feature selection algorithms FCBF, Chi-Square, and ReliefF are selected due their better performance, and applied on three different studentâ��s data sets. …”
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Investigation of relaxation factor in landweber iterative algorithm for electrical capacitance tomography
Published 2020“…It is crucial to select a suitable relaxation factor in iterative image reconstruction algorithms (e.g. …”
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Design of intelligent Qira’at identification algorithm
Published 2017“…The process of the SPAP Algorithm is to extend parameters of the Affine Projection Block with two different selections of windowing length that affect the final accuracy on pattern classification. …”
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9
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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10
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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11
Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…Prediction, identification, understanding and visualization of relationship between factors affecting mortality in ACS patients using feature selection and ML algorithms. …”
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12
Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…This condition is attributed to the increasing number of audit data features and the decreasing performance of human-based smart intrusion detection systems regarding classification accuracy, false alarm rate, and classification time. Feature selection and classifier parameter tuning are important factors that affect the performance of any intrusion detection system. …”
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Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Development of gesture database for an adaptive gesture recognition system
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
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Analyzing CT images for detecting lung cancer by applying the computational intelligence-based optimization techniques
Published 2022“…The gathered image noise is removed by applying the mean filter, and the affected regions are segmented with the help of the Butterfly Optimization Algorithm-based K-Means Clustering (BOAKMC)algorithm. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar
Published 2021“…This algorithms were selected based on previous literature review in price prediction. …”
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Optimization of chest X-ray exposure factors using machine learning algorithm
Published 2023“…The role of BMI in the selection of radiation exposure factors (kVp, mAs) was evaluated. …”
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Optimization of stiffened panel fatigue life by using finite element analysis
Published 2020“…The screening approach that is the random sampling method was able to select design points close to the objective. The multi-objective genetic algorithm which selects the design points based on Pareto optimal design combined with the adaptive multi-objective algorithm method which uses an optimal space-filling was shown to be efficient for time limitation and budget. …”
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An improved diabetes risk prediction framework : An Indonesian case study
Published 2018“…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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