Search Results - (( _ classification (problems OR problem) algorithm ) OR ( data visualization using algorithm ))
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Classification of strategies for solving programming problems using Aol sequence analysis
Published 2019“…This eye tracking study examines participants’ visual attention when solving algorithmic problems in the form of programming problems. …”
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Conference or Workshop Item -
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Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin
Published 2020“…Therefore, the chosen technique is classification and the algorithm that will be applied in the classification process is Linear Support Vector Machines (LSVM). …”
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Thesis -
3
Development of Technical Safety Dashboard Using Microsoft Power BI Integration with R
Published 2020“…Besides, this paper also enlightens on one of the Machine Learning tools used which is R, with the utilization of K Nearest Neighbor (KNN) algorithm as method of classification for data. …”
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Final Year Project -
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A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping
Published 2016“…The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. …”
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Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm
Published 2010“…WEKA program application was used for main chain angles (Phi and Psi) data classification. …”
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7
Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…Then, a Machine Learning Algorithm (MLA) is used to train and test the data before a classifier is used to classify the new incoming dataset. …”
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Proceeding Paper -
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Comparative analysis of danger theory variants in measuring risk level for text spam messages
Published 2024journal::journal article -
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…Criminal risk is predicted using classification models for a particular time interval and place. …”
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…The development of ML algorithms in dermatology has been supported lately regarding links to digital data processing (e.g., electronic medical records, Image Archives, omics), quicker computing and cheaper data storage. …”
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Article -
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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12
Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…This project can be improved by making a comparative study on Artificial Immune System and other techniques or algorithms used to solve dengue classification problems.…”
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Detection of the river sediment deposition area at Kuala Perlis river mouth using Landsat 8 OLI within the years 2019, 2020 and 2021 / Nur Zakira Ain Zamrun
Published 2022“…Quantification of Landsat 8 OLI satellite images was applied using ENVI software on the study area for detecting sedimentation in the study area that used image data band correlation in deposited river sediment through unsupervised classifier algorithm and selection of spectral bands for MNDWI. …”
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Thesis -
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Algorithms of Classification of Mass Problems of Production Subject Domains
Published 2019“…This paper develops the algorithms for classification of mass problems of production subject domains. …”
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A derivative-free optimization method for solving classification problem
Published 2010“…The results of numerical experiments allowed us to say the proposed algorithms are effective for solving classification problems at least for databases considered in this study.…”
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Article -
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…The focus of this thesis is on solvingclustering and classification problems. Specifically, we will focus on new optimization methods for solving clustering and classification problems. …”
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Thesis -
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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Article -
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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Article -
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Classification for large number of variables with two imbalanced groups
Published 2020“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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Thesis
