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1
Frequent patterns minning of stock data using hybrid clustering association algorithm
Published 2009“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data. …”
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2
MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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3
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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4
MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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5
Pattern discovery using k-means algorithm
Published 2014“…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
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6
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
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7
Sequential pattern mining using PrefixSpan with pseudoprojection and separator database
Published 2008“…Sequential pattern mining is a new branch of data mining science that solves inter-transaction pattern mining problems. …”
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8
Pattern Discovery Using K-Means Algorithm
Published 2024“…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
Proceedings Paper -
9
Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor
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10
Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor
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11
An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP
Published 2007“…The algorithm, however, has to posess a high performance characteristic. …”
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12
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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13
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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14
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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15
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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16
HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…The algorithm gives a mean accuracy of 84% out of 125 test images.…”
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Final Year Project -
17
Beamforming Algorithms for Adaptive Array Antenna
Published 2014“…The algorithms are applied to a 3-faceted adaptive array antenna. …”
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18
Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering
Published 2021“…In the field of computer science, data mining facilitates the extraction of useful knowledge and patterns from a huge amount of data. Various techniques exist in the data mining domain to explore the links, associations, and patterns from data in data warehouses. …”
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19
Finding spatio-temporal patterns in climate data using clustering
Published 2005“…In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering climate data. …”
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20
Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…Consequently, to handle these data, computer algorithms must adapt to their characteristics. Due to its massive volume, variety, and velocity, it contains a lot of insightful patterns. …”
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