Search Results - (( software optimization method algorithm ) OR ( data classification learning algorithm ))
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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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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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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…However, the classification algorithm cannotclassify data optimally due to the challenges in dealing with variousdata sets. …”
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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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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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
Published 2014“…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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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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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“…One of the outstanding classifications methods in data mining is support vector machine classification (SVM). …”
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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection
Published 2023“…During the training and optimization process, these base learners adopt a hybrid BP and Particle Swarm Optimization algorithm to combine both local and global optimization capabilities for identifying optimal features and improving the classification performance. …”
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Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach
Published 2023“…The focus of this study is on the use of DTs, employing the Classification and Regression Trees (CART) algorithm, in the initial screening of athletes. …”
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A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS
Published 2019“…The methods to implement this project is through data collection, feature extraction, feature selection, and classification process. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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Radiomics analysis and supervised machine learning model for classification of cervical cancer images using diffusion weighted imaging-MRI
Published 2024“…Additionally, the SVM algorithm was evaluated based on its performance across different DWI bvalues, aiming to optimize scanning time. …”
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Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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