Search Results - (( software optimization method algorithm ) OR ( learning classification using 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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Training functional link neural network with ant lion optimizer
Published 2020“…This paper proposed the implementation of Ant Lion Algorithm as learning algorithm to train the FLNN for classification tasks. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…Optimization algorithms are widely used for the identification of intrusion. …”
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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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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. This study used 1,538 data samples from Goldman Osteometric Dataset which consisted of femur, humerus and tibia parts. …”
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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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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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
Published 2014“…The proposed method is applied to 14 real world dataset from the machine learning repository. The algorithm’s performance is illustrated by the corresponding table of the classification rate. …”
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A direct ensemble classifier for imbalanced multiclass learning
Published 2012“…Researchers have shown that although traditional direct classifier algorithm can be easily applied to multiclass classification, the performance of a single classifier is decreased with the existence of imbalance data in multiclass classification tasks.Thus, ensemble of classifiers has emerged as one of the hot topics in multiclass classification tasks for imbalance problem for data mining and machine learning domain.Ensemble learning is an effective technique that has increasingly been adopted to combine multiple learning algorithms to improve overall prediction accuraciesand may outperform any single sophisticated classifiers.In this paper, an ensemble learner called a Direct Ensemble Classifier for Imbalanced Multiclass Learning (DECIML) that combines simple nearest neighbour and Naive Bayes algorithms is proposed. …”
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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection
Published 2023“…DL models often use gradient descent optimization, i.e., the Back-Propagation (BP) algorithm; therefore, their training and optimization procedures suffer from local sub-optimal solutions. …”
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A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection
Published 2023“…Two datasets from UCI machine learning were used: Website Phishing Dataset and Phishing Websites Dataset. …”
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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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Support directional shifting vector: A direction based machine learning classifier
Published 2021“…There exist several types of classification algorithms, and these are based on various bases. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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Analysis Of Personal Protective Equipment Classification Method Using Deep Learning
Published 2022“…This classification is performed using Anaconda and Jupyter Notebok Software that use Python as the programming language. …”
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Undergraduates Project Papers -
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Condition diagnosis of bearing system using multiple classifiers of ANNs and adaptive probabilities in genetic algorithms
Published 2014“…The mANNs are used to provide several best initial weights which are optimized by APGAs.The set optimized weights from APGAs, afterward, are used as the best weights for condition diagnosis. …”
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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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A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS
Published 2019“…The machine learning algorithm is used to train and test datasets with the percentage of 70% which is 140 samples from malware and benign applications and 30% of total datasets which is 60 samples from malware and benign applications respectively. …”
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Final Year Project Report / IMRAD
