Search Results - (( variable discriminant using algorithm ) OR ( java location based algorithm ))
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…Next, the weighted and transformed features were used to train Linear Discriminant Function (LDA) and to evaluate the constructed rule. …”
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Group formation using genetic algorithm
Published 2009“…However, due to lack of programming skills especially in Java programming language and the inability to have meetings frequently among the group members,most of the students’ software project cannot be delivered successfully.To solve this problem, systematic group formation is one of the initial factors that should be considered to ensure that every group consists of quality individuals who are good in Java programming and also to ensure that every group member in a group are staying closer to each other.In this research, we propose a method for group formation using Genetic Algorithms, where the members for each group will be generated based on the students’ programming skill and location of residential colleges.…”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…The correlation of each system calls are examined using coefficient correlations of each selected system call variables. …”
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Fault diagnostic algorithm for precut fractionation column
Published 2004“…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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Multi-floor indoor location estimation system based on wireless local area network
Published 2007“…The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. Estimated location is reported as physical location and symbolic location. …”
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Classification for large number of variables with two imbalanced groups
Published 2020“…The difference between the two algorithms is in terms of the order of resampling and variable extraction prior to the construction of linear discriminant analysis (LDA). …”
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Strategies of Handling Different Variables Reduction for LDA
Published 2012“…The variables selection technique with local searching algorithm is manipulated. …”
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Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0
Published 2023“…In this project, Fornell-Larker parameters are used to test the measurement algorithm for the research's discriminant validity. 380 valid questionnaires returnedback and conducted the calculation of the algorithm's assessment to constructs' validity and realibility assessment, discriminant validity using HTMTand Fornell-Larker approaches. …”
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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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Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit
Published 2025“…Several machine learning algorithms which are decision tree, linear discriminant, na�ve Bayes, support vector machines, k-nearest neighbor, AdaBoost, and random forest were used for the classification. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Campus safe: Safeguarding GPS-based Physical Identity and Access Management (PIAM) system with a lightweight Geo-Encryption
Published 2022“…Subsequently, this project embedded with a lightweight Geo-Encryption algorithm to preserve the privacy of real-time GPS location. …”
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Academic Exercise -
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Machine learning classifications of multiple organ failures in a malaysian intensive care unit
Published 2024“…Several machine learning algorithms which are decision tree, linear discriminant, naïve Bayes, support vector machines, k-nearest neighbor, AdaBoost, and random forest were used for the classification. …”
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Optimized conditioning factors using machine learning techniques for groundwater potential mapping
Published 2019“…In addition, 917 spring locations were identified and used to train and test three machine learning algorithms, namely Mixture Discriminant Analysis (MDA), Linear Discriminant Analysis (LDA) and Random Forest (RF). …”
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Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The first algorithm locates interest points in food images using an MSER. …”
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Water Quality Index Using Modified Random Forest Technique: Assessing Novel Input Features
Published 2024journal::journal article -
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The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach
Published 2018“…Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the performance variables tested. …”
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A study on advanced statistical analysis for network anomaly detection
Published 2005“…The correlation of each system calls are examined using coefficient correlations of each selected system call variables. …”
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