Search Results - (( simulation classification mining algorithm ) OR ( program segmentation using algorithm ))
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. …”
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Framework for mining XML format business process log data
Published 2024“…Therefore, a lot of frequent subtree mining (FSM) algorithms and methods were developed to get information from semi-structured data specifically data with hierarchical nature. …”
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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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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction
Published 2024“…Most computer applications use machine learning and data mining techniques to aid classification and prediction of a disease. …”
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Discretization of integrated moment invariants for writer identification
Published 2008“…Hence, an incorporated scaling factor of geometric functions into United Moment Invariant function is proposed for mining the feature of unconstrained words. Subsequently, the discrete proposed features undertake discretization procedure prior to classification for better feature representation and splendid classification accuracy. …”
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Improving Classification Accuracy of Scikit-learn Classifiers with Discrete Fuzzy Interval Values
Published 2020“…Understanding machine learning (ML) algorithm from scratch is time consuming. Thus, many software and library packages such as Weka and Scikit-Learn have been introduced to help researchers run simulation on several amounts of well-known classifiers. …”
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RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm
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Development Of Semi-Automatic Liver Segmentation Method For Three-Dimensional Computed Tomography Dataset
Published 2017“…In post-processing, the contour of liver is smooth by binary Gaussian filter. The liver segmentation program with proposed algorithm is evaluated with CT datasets obtained from SLIVER07 to prove its effectiveness in liver segmentation. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altart...
Published 2023“…Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. …”
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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu
Published 2005“…The project used Back-propagation Neural Network for the algorithm to classified images. …”
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Word segmentation of output response for sign language devices
Published 2020“…The proposed text segmentation method in this work is by using the dynamic programming and back-off algorithm, together with the probability score using word matching with an English language text corpus. …”
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Supervised retinal vessel segmentation based on neural network using broader aging dataset
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Interactive blood vessel segmentation from retinal fundus image based on canny edge detector
Published 2021“…The program will draw out the vessel edges. After that, those vessel edges will be segmented to bring focus on its details or detect the abnormal vessel. …”
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Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging
Published 2022“…Results: Image segmentation using the DP-AC algorithm enhanced the visibility of the image features in the region of interest while suppressing the image’s background noise. …”
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