Search Results - (( software optimization method algorithm ) OR ( parameter classification learning algorithm ))
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Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…The classification algorithm is a popular machine learning approach for software defect prediction. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network
Published 2020“…This was to obtain a good combination of parameters in order to produce a better gender classification. …”
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…This article presents the development of an improved intrusion detection method for binary classification. In the proposed IDS, Rao Optimization Algorithm, Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) were combined with NTLBO algorithm with supervised ML techniques (for feature subset selection (FSS). …”
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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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A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…It is capable of envisaging results and mostly effective than other classification methods. The SVM is a one technique of machine learning techniques that is well known technique, learning with supervised and have been applied perfectly to a vary problems of: regression, classification, and clustering in diverse domains such as gene expression, web text mining. …”
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A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection
Published 2023“…However, it is hard to determine the fuzzy parameter manually in a complex problem, and the process of generating the parameter is called fuzzy modelling. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…This proposed classifier achieved 97.9% classification accuracy on the ISIC dataset. 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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Analysis Of Personal Protective Equipment Classification Method Using Deep Learning
Published 2022“…Based on the result, CNN algorithm is a good algorithm as the binary classification of PPE achieved high accuracy result.…”
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Undergraduates Project Papers -
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Modified anfis architecture with less computational complexities for classification problems
Published 2018“…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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Condition diagnosis of bearing system using multiple classifiers of ANNs and adaptive probabilities in genetic algorithms
Published 2014“…Artificial Neural Networks (ANNs) are one of the most popular methods for classification in condition diagnosis of bearing systems.Regarding to ANNs performance, ANNs parameters have important role especially connectivity weights.In several running of learning processes with the same structure of ANNs, we can obtain different accuracy significantly since initial weights are selected randomly. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…In the future, different types of deep learning algorithms need to be applied, and different datasets can be tested with different hyper-parameters to produce more accurate ASD classifications.…”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…In this paper, an evaluation for these transfer learning to be applied in wafer defect detection. The objective is to establish the best transfer learning algorithms with a known baseline parameter for Wafer Defect Detection. …”
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Conference or Workshop Item -
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Adaptive parameter control strategy for ant-miner classification algorithm
Published 2020“…This criterion is responsible for adding only the important terms to each rule, thus discarding noisy data. The ACS algorithm is designed to optimize the IR parameter during the learning process of the Ant-Miner algorithm. …”
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Development of an intelligent prediction tool for rice yield based on machine learning techniques
Published 2006“…Support vector machine algorithm is developed for classification of rice plantation data. …”
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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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Classification of Planetary Nebulae through Deep Transfer Learning
Published 2020“…It focusses on distinguishing PNe from other types of objects, as well as their morphological classification. We adopted the deep transfer learning approach using three ImageNet pre-trained algorithms. …”
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