Search Results - (( using optimization mining algorithm ) OR ( using evaluation process algorithm ))
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Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah
Published 2013“…In addition, two novel optimization methods are developed and presented which are named the mine blast algorithm (MBA) and the water cycle algorithm (WCA). …”
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Dissimilarity algorithm on conceptual graphs to mine text outliers
Published 2009“…The graphical text representation method such as Conceptual Graphs (CGs) attempts to capture the structure and semantics of documents.As such, they are the preferred text representation approach for a wide range of problems namely in natural language processing, information retrieval and text mining.In a number of these applications, it is necessary to measure the dissimilarity (or similarity) between knowledge represented in the CGs.In this paper, we would like to present a dissimilarity algorithm to detect outliers from a collection of text represented with Conceptual Graph Interchange Format (CGIF).In order to avoid the NP-complete problem of graph matching algorithm, we introduce the use of a standard CG in the dissimilarity computation.We evaluate our method in the context of analyzing real world financial statements for identifying outlying performance indicators.For evaluation purposes, we compare the proposed dissimilarity function with a dice-coefficient similarity function used in a related previous work.Experimental results indicate that our method outperforms the existing method and correlates better to human judgements. …”
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An enhanced version of black hole algorithm via levy flight for optimization and data lustering problems
Published 2019“…The processes of retrieving useful information from a dataset are an important data mining technique that is commonly applied, known as Data Clustering. …”
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Improved building roof type classification using correlation-based feature selection and gain ratio algorithms
Published 2017“…First, the feature importance was evaluated using gain ratio algorithm, and the result was ranked, leading to selection of the optimal feature subset. …”
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An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems
Published 2019“…The processes of retrieving useful information from a dataset are an important data mining technique that is commonly applied, known as Data Clustering. …”
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Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Six machine learning algorithms were applied and compared based on the classification evaluation methods. …”
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Final Year Project / Dissertation / Thesis -
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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A Hybrid Evaluation Metric for Optimizing Classifier
Published 2011“…However, the use of accuracy metric leads the searching process to the sub-optimal solutions due to its limited capability of discriminating values. …”
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A hybrid evaluation metric for optimizing classifier
Published 2011“…However, the use of accuracy metric leads the searching process to the sub-optimal solutions due to its limited capability of discriminating values. …”
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The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data
Published 2024“…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection
Published 2024“…This study examines the optimization of Indonesian text sentiment analysis through the integration of feature selection using a genetic algorithm (GA) with deep learning models. …”
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Evaluating integrated weight linear method to class imbalanced learning in video data
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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A Performance Evaluation of Chi-Square Pruning Techniques in Class Association Rules Optimization
Published 2018“…The performance of associative classification is relied on the classification where the classification is worked based on the class association rules which generated from frequent rule mining process. To optimize the frequent itemsets based on the support value, in this research, we proposed a new optimization pruning technique to prune decision tree according to the correlation of each decision tree branches using genetic algorithm. …”
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A Performance Evaluation of Chi-Square Pruning Techniques in Class Association Rules Optimization
Published 2018“…The performance of associative classification is relied on the classification where the classification is worked based on the class association rules which generated from frequent rule mining process. To optimize the frequent itemsets based on the support value, in this research, we proposed a new optimization pruning technique to prune decision tree according to the correlation of each decision tree branches using genetic algorithm. …”
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Portfolio optimization with percentage error-based fuzzy random data for industrial production
Published 2024“…The proposed framework not only acknowledges the importance of data preprocessing but also offers a systematic approach to processing fuzzy random data, thus providing a robust foundation for portfolio selection algorithms. …”
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Portfolio optimization with percentage error-based fuzzy random data for industrial production
Published 2024“…The proposed framework not only acknowledges the importance of data preprocessing but also offers a systematic approach to processing fuzzy random data, thus providing a robust foundation for portfolio selection algorithms. …”
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