Search Results - (( its application means algorithm ) OR ( _ modification mining algorithm ))
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Modifying iEclat algorithm for infrequent patterns mining
Published 2018“…A few parts of this algorithm need a modification to assure that it is suitable for mining infrequent pattern. …”
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Modifying iEclat algo ithm for infrequent patterns mining
Published 2018“…A few parts of this algorithm need a modification to assure that it is suitable for mining infrequent pattern. …”
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An improved ACS algorithm for data clustering
Published 2020“…To improve the ACOC, this study proposes a modified ACOC, called M-ACOC, which has a modification rate parameter that controls the convergence of the algorithm. …”
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Classification of stock market index based on predictive fuzzy decision tree
Published 2005“…In particular, predictive FDT algorithm is based on the concept of degree of importance of attribute contributing to the classification. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…Many statistical and data mining techniques have been used to predict time series stock market. …”
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Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem
Published 2022“…It is also used extensively in experiments to test the performances of metaheuristic algorithms and their hybrids. For example, Tabu Search (TS) has been successfully hybridized with other techniques, including particle swarm optimization (PSO) algorithm and the two-stage TS algorithm to solve MKP. …”
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An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets
Published 2021“…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets
Published 2021“…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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Data clustering using the bees algorithm
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Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering
Published 2024“…The fuzzy C-ordered-means clustering (FCOM) is a fuzzy clustering algorithm that enhances robustness and clustering accuracy through the ordered mechanism based on fuzzy C-means (FCM). …”
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A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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All-pass filtered x least mean square algorithm for narrowband active noise control
Published 2018“…The results also show that the proposed method outperforms other LMS algorithm without secondary path modelling. The proposed narrowband LMS algorithm would benefit in the design of efficient feedforward ANC system that can realize noise control in air intake duct applications.…”
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Enhanced Automated Framework For Cattle Tracking And Classification
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Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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Final Year Project
