Search Results - (( java implication force algorithm ) OR ( data features selection algorithm ))

Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

“…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…Feature selection and classification are widely utilized for data analysis. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Feature selection for high dimensional data: An evolutionary filter approach. by Yahya, Anwar Ali, Osman, Addin, Ramli, Abdul Rahman, Balola, Adlan

“…Approach: In this study, we proposed an adapted version of genetic algorithm that can be applied for feature selection in high dimensional data. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

“…Thus, to solve these problems, feature selection can be used to select optimal subset of features and reduce the data dimensionality. …”
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A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

“…In this thesis, a novel weighted feature selection approach on nominal features is proposed, for a partition. clustering algorithm that can handle mixed data. …”
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Comparing the performance of FCBF, Chi-Square and relief-F filter feature selection algorithms in educational data mining by Zaffar, M., Hashmani, M.A., Savita, K.S.

“…It is very necessary to increase the quality of dataset as to get better prediction results. There are many feature selection algorithms, however three filter feature selection algorithms FCBF, Chi-Square, and ReliefF are selected due their better performance, and applied on three different studentâ��s data sets. …”
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Comparing the performance of FCBF, Chi-Square and relief-F filter feature selection algorithms in educational data mining by Zaffar, M., Hashmani, M.A., Savita, K.S.

“…It is very necessary to increase the quality of dataset as to get better prediction results. There are many feature selection algorithms, however three filter feature selection algorithms FCBF, Chi-Square, and ReliefF are selected due their better performance, and applied on three different studentâ��s data sets. …”
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Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

“…However, these semisupervised multitask selection feature algorithms are unable to naturally handle the multiview data since they are designed to deal single-view data. …”
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Performance analysis of feature selection algorithm for educational data mining by Zaffar, M., Hashmani, M.A., Savita, K.S.

“…This paper present an analysis of the performance of feature selection algorithms on student data set. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

“…Selecting the relevant features from the data leads to better classification results. …”
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

“…However this feature selection algorithm might be unstable due to the stochastic property of GA. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…One of the main steps after the data collection stage of any method is selecting a subset of the features to be used for the feature selection process. …”
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Optimization of attribute selection model using bio-inspired algorithms by Basir, Mohammad Aizat, Yusof, Yuhanis, Hussin, Mohamed Saifullah

“…Attribute selection which is also known as feature selection is an essential process that is relevant to predictive analysis.To date, various feature selection algorithms have been introduced, nevertheless they all work independently. …”
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Naive bayes-guided bat algorithm for feature selection. by Taha, Ahmed Majid, Mustapha, Aida, Chen, Soong Der

“…The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. …”
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A study of feature selection algorithms for predicting students academic performance by Zaffar, M., Savita, K.S., Hashmani, M.A., Rizvi, S.S.H.

“…In the light of this mentioned fact, it is necessary to choose a feature selection algorithm carefully. This paper presents an analysis of the performance of filter feature selection algorithms and classification algorithms on two different student datasets. …”
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A study of feature selection algorithms for predicting students academic performance by Zaffar, M., Savita, K.S., Hashmani, M.A., Rizvi, S.S.H.

“…In the light of this mentioned fact, it is necessary to choose a feature selection algorithm carefully. This paper presents an analysis of the performance of filter feature selection algorithms and classification algorithms on two different student datasets. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…In its operation, the metaheuristic algorithm optimizes the feature selection process,which will later be processed using the classification algorithm.Three (3) meta-heuristics were implemented, namely Genetic Algorithm, Particle Swarm Optimization, and Cuckoo Search Algorithm; the experiment was conducted, and the results were collected and analyzed. …”
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Metaheuristic algorithms for feature selection (2014–2024) by Faizan, Muhammad, Muhammad Arif, Mohamad

“…Feature selection is a process used during machine learning and data analysis, aimed at selecting the best features to increase model efficiency, decrease complexity, and increase readability. …”
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