Search Results - (( java implementation learning algorithm ) OR ( parameter implementation svm algorithm ))
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Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study
Published 2020“…Proposed formulations on SVM regularization parameter provides synergistic adjustments between prediction or classification accuracy and the level of correlations among features in the SVM implemented. …”
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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An Arabic hadith text classification model using convolutional neural network and support vector machine / Mohd Irwan Mazlin
Published 2022“…Second, parameter tuning is conducted to find the best parameter for CNN-SVM. …”
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4
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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Classification of basal stem rot disease in oil palm using dielectric spectroscopy
Published 2018“…Without implementing any data reduction algorithm, the highest classification accuracy was found in SVM classifier with 79.55%. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Furthermore, using SVM requires the user to set certain parameters values, including kernel type and kernel parameters, since these parameters own a significant effect on the effectiveness of SVM. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…In this research, two machine learning models, Deep Neural Network (DNN) and Support Vector Machine (SVM), are utilized for sound classification. Both models' parameters are optimized to achieve optimal performance. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…The CNN algorithm produces better results with an accuracy of 97.07%, compared with the SVM algorithm. …”
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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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Hospital site suitability assessment using three machine learning approaches: evidence from the Gaza strip in Palestine
Published 2021“…Identification of the most significant parameters (conditioning factors) that influence a suitable hospital location was achieved by employing correlation-based feature selection (CFS) with the search algorithm (greedy stepwise). …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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15
The formulation of a transfer learning pipeline for the classification of the wafer defects
Published 2023“…Thus, this study will aim to explore 17 types of TL models, and classify the features extracted using 3 different ML algorithms, namely Support Vector Machine (SVM), k-Nearest Neighbor (kNN) and Random Forest (RF). …”
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Real-time human activity recognition using external and internal spatial features
Published 2010“…Activities are classified by a support vector machine (SVM) with a radial basis kernel. Optimal parameters for the SVM are found through a 10-fold cross-validation. …”
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Proceeding Paper -
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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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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Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar
Published 2012“…In this research, Multilayer perception (MLP) of feedforward Artificial Neural Network (ANN) has also been used as the classifier and comparison are made between the SVM and ANN method. The SVM results show that RBF kernel is superior to linear kernel in classifying the transient with average percentage of 83% This research has also proved that SVM has higher performance than the backpropagation algorithm of the ANN.…”
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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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