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1
Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…An algorithm called Flex (Frequent lexicographic patterns) has been proposed in obtaining a good performance of searching li-equent patterns. …”
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Thesis -
2
Sequential pattern mining using PrefixSpan with pseudoprojection and separator database
Published 2008“…Future research includes exploring the use of Separator Database in PrefixSpan with pseudoprojection to improve mining constrained sequential patterns. …”
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Conference or Workshop Item -
3
Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…A comprehensive performance study has been reported that PrefixSpan, one of the sequential pattern mining algorithms, outperforms GSP, SPADE, as well as FreeSpan in most cases, and PrefixSpan integrated with pseudoprojection technique is the fastest among those tested algorithms. …”
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4
Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…A comprehensive performance study has been reported that PrefixSpan, one of the sequential pattern mining algorithms, outperforms GSP, SPADE, as well as FreeSpan in most cases, and PrefixSpan integrated with pseudoprojection technique is the fastest among those tested algorithms. …”
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Thesis -
5
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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6
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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7
Sistem Pengecaman Bentuk Berdasarkan FPGA
Published 2005“…It is always can be an application to whatever course and now have been used widely among the people. Hence, a pattern recognition system by an array of chemical sensor application will be developing based on FPGA. …”
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Monograph -
8
An efficient fuzzy C-least median clustering algorithm
Published 2021“…In this paper we are discussing our new procedure for clustering called Fuzzy C-least median of squares algorithm which is an improvement to Fuzzy C-means (FCM) algorithm. …”
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9
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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10
The effect of job satisfaction on the relationship between organizational culture and organizational performance
Published 2023“…The statistical tools (Absolute Mean Error & Fried Man) are used to rank the performance of all algorithms. …”
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11
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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12
Modeling of vehicle trajectory clustering based on LCSS for traffic pattern extraction
Published 2017“…Hence, with the advancement of the available vehicle tracking system, vehicle trajectory dataset is selected as suitable candidate input for the traffic pattern extraction. The implementation of k-means and fuzzy c-means (FCM) clustering algorithm for vehicle flow analyzing task is served as focus in this paper. …”
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Proceedings -
13
A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm
Published 2024journal::journal article -
14
A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…Size was extracted using Extreme Point Detection algorithm and Hit or Miss Transformation method was used to extract the stroke formation pattern. …”
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Thesis -
15
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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16
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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17
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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18
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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19
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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20
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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