Search Results - (( based selection method algorithm ) OR ( using solution mining algorithm ))
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A partition based feature selection approach for mixed data clustering / Ashish Dutt
Published 2020“…One such pre-processing algorithm in EDM is clustering. It is a widely used method in data mining to discover unique patterns in underlying data. …”
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Tree-based contrast subspace mining method
Published 2020“…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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3
Ideal combination feature selection model for classification problem based on bio-inspired approach
Published 2020“…The important step is to idealize the combined feature selection models by finding the best combination of search method and feature selection algorithms. …”
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Book Section -
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Arabic Text Clustering Methods And Suggested Solutions For Theme-based Quran Clustering: Analysis Of Literature
Published 2024journal::journal article -
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Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques
Published 2014“…The aim is to solve the above-mentioned problems via an optimization mechanism based upon the combination between runtime path prediction method and heuristic algorithms. …”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO
Published 2014“…Therefore, it can be solved by using population-based techniques such as Genetic Algorithm and Particle Swarm Optimization. …”
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Towards a better feature subset selection approach
Published 2010“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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9
Evolving fuzzy grammar for crime texts categorization
Published 2015“…Machine learning (ML) based methods are the popular solution for this problem. …”
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Article -
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Identifying Features Eligiblity For Blood Donors' Preferences Using Artificial Neural Networks Prediction Performances
Published 2017“…Furthermore, blood donors’ preferences are based on human opinions, which could cause different priority, conditions, and data retrieval method based on different communities, organisation, or places. …”
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11
Accelerated mine blast algorithm for ANFIS training for solving classification problems
Published 2016“…Mine Blast Algorithm (MBA) is newly developed metaheuristic technique. …”
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Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman
Published 2016“…The critical factors of complexity at application level include data size and data rate of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates and learning modes, and the adoption of data mining algorithms. …”
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A numerical method for frequent pattern mining
Published 2009“…The PC_Miner algorithm traverses the PC_Tree by using an efficient pruning technique. …”
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Data Classification and Its Application in Credit Card Approval
Published 2004“…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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Final Year Project -
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Towards scalable algorithm for closed itemset mining in high-dimensional data
Published 2017“…Unlike many well-known algorithms, BFF traverses the search tree in breadth-first manner resulted to a minimum use of memory and less running time. …”
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A comprehensive analysis of blockchain-based cryptocurrency mining impact on energy consumption
Published 2022“…The Proof-of-Work (PoW) algorithm is used for mining ‘Bitcoin’ which is consumed enormous computational power. …”
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Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah
Published 2013“…Metaheuristic algorithms have been extensively used in numerous domains especially in engineering. …”
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A multi-layer dimension reduction algorithm for text mining of news in forex / Arman Khadjeh Nassirtoussi
Published 2015“…Every context requires its own customized text mining algorithms in order to achieve best results. …”
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Medical diagnosis using data mining techniques / Shaiful Nizam Zamri
Published 2003“…Medical Diagnosis Using Data Mining Techniques is a system in specifically facilitates the data mining techniques in predicting the appropriate drug prescription of certain condition of patients. …”
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