Search Results - (( features solution learning algorithm ) OR ( java application testing algorithm ))
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Metaheuristic algorithms for feature selection (2014–2024)
Published 2025“…Metaheuristic algorithms are suited to provide solutions to feature selection problems because these problems are combinatorial and require an effective and efficient search through large solution spaces. …”
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RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…In addition, it is considered that existing solutions do not provide a feature driftaware solution to the concept drift adaptable solution, which exploits the fact that many of the original features are non-relevant. …”
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…The comprehensive experiments results show that the proposed algorithm outperforms all other algorithms in terms of sentiment analysis classification accuracy through finding the best solutions, while its also minimizes the number of selected features. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.…”
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Security alert framework using dynamic tweet-based features for phishing detection on twitter
Published 2019“…However, it is observed that there are only a few machine learning solutions to detect phishing attacks on OSNs are being proposed and implemented. …”
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8
K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm
Published 2025“…As proven by the obtained results, integrating feature selection with ensemble learning is effective for phishing detection; moreover, the scalability and efficiency of such a solution in real-world applications are demonstrated.…”
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A new experiential learning electromagnetism-like mechanism for numerical optimization
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Crossover and mutation operators of genetic algorithms
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Enhancement of feature sets for subjectivity analysis on Malay-English code-switching text
Published 2023“…In the unified code-switching feature set, the extracted Malay and English features were unified using an adapted algorithm known as the Malay-English Unified POS. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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A new experiential learning electromagnetism-like mechanism for numerical optimization
Published 2017“…A new Experiential Learning Electromagnetism-like Mechanism algorithm (ELEM) is proposed in this paper. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…Moreover, K-Nearest Neighbor (KNN) classifier was used to evaluate the effectiveness of the features identified by the proposed SCSO algorithm. …”
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Crossover and mutation operators of genetic algorithms
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An improved bees algorithm local search mechanism for numerical dataset
Published 2015“…Furthermore, in this study the feature selection algorithm is implemented and tested using most popular dataset from Machine Learning Repository (UCI). …”
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…So,the selection of features is minimaland is not based on the previous learning process or what is known as heuristics. …”
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Underwater Image Recognition using Machine Learning
Published 2024“…A Convolutional Neural Network (CNN) is a type of a deep learned an algorithm that has been created for image processing when using convolutional layers to automatically and in a hierarchical way learn features from the input images. …”
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Indoor occupancy detection using machine learning and environmental sensors / Akindele Segun Afolabi ... [et al.]
Published 2025“…In this paper, three algorithms were developed: the first was for outlier removal from features, the second was for feature selection, and the third was for partial-features-availability-aware ML model selection. …”
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