Search Results - (( pattern ((means algorithm) OR (based algorithm)) ) OR ( pattern using algorithms ))
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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2
Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering
Published 2021“…In this paper, we have compared the performance of K-Mean and XMean clustering algorithms using two datasets of student enrollment in higher education institutions. …”
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3
Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. Nonetheless, the process of detecting anomalies in streaming data is laborious. …”
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5
Pattern Classification of Human Epithelial Images
Published 2016“…Last but not least, from the mean of properties, it will classify into the pattern after ranging the value of mean properties of each of the pattern itself that has been done in classification stage.…”
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Final Year Project -
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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Customer segmentation on clustering algorithms
Published 2023“…This report presents an analysis of customer segmentation using various clustering algorithms, including k-means, DBSCAN, GMM, and RFM. …”
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A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques
Published 2014“…Clustering analysis has been considered as a useful means for identifying patterns in dataset. …”
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Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control
Published 2020“…Addition of hybrid automata algorithm to run pattern and non-pattern recognition based control methods is an advantage to increase accuracy in differentiating forward stroke or hand return activity. …”
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10
Clustering of rainfall data using k-means algorithm
Published 2019“…K-Means algorithm is used to obtain optimal rainfall clusters. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…The best mapping percentage of 62.7 obtained using the proposed algorithm when k = 15 is obtained to outperform the performance of the generic k-means. …”
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12
Clustering Spatial Data Using a Kernel-Based Algorithm
Published 2005“…Therefore, this work comes up with new clustering algorithm using kernel-based methods for effective and efficient data analysis by exploring structures in the data.…”
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13
Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
Published 2023“…The statistical tools (Absolute Mean Error & Fried Man) are used to rank the performance of all algorithms. …”
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14
Acoustic echo cancellation using adaptive filtering algorithms for quranic accents (Qiraat) identification
Published 2015“…In order to conduct the AEC, three adaptive algorithms known as affine projection (AP), least mean square (LMS), and recursive least squares (RLS) are used during the preprocessing phase. …”
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Facial image retrieval on semantic features using adaptive mean genetic algorithm
Published 2019“…Finally, the features are selected using Adaptive Mean Genetic Algorithm (AMGA). In this study, the average PSNR value obtained after applying Wiener filter was 45.29. …”
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16
Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…The best mapping percentage of 62.7 obtained using the proposed algorithm when k = 15 is obtained to outperform the performance of the generic k-means. …”
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17
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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18
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan
Published 2019“…Which is why this project objective is to develop a web based clustering tool using K-MEAN++ algorithm. This project will use the rapid application development (RAD) methodology since this are the most suitable method for developing the system. …”
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