Search Results - (( developing using clustering algorithm ) OR ( java implementation mining algorithm ))
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1
Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Thesis -
2
A web-based implementation of k-means algorithms
Published 2022“…The project was planned using the Kanban development methodology, and was built using HTML, CSS, JavaScript, Django, NumPy and pandas. …”
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Final Year Project / Dissertation / Thesis -
3
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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4
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Article -
5
Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Conference or Workshop Item -
6
Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Conference or Workshop Item -
7
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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8
Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…So far, limited genetic-based clustering ensemble algorithms have been developed. …”
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9
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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10
MuDi-Stream: A multi density clustering algorithm for evolving data stream
Published 2016“…Density-based method has emerged as a worthwhile class for clustering data streams. Recently, a number of density-based algorithms have been developed for clustering data streams. …”
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Article -
11
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Thesis -
12
Data clustering using the bees algorithm
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Conference or Workshop Item -
13
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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14
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. …”
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15
A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds
Published 2007“…In this work a fuzzy hierarchical algorithm is developed which provides a mechanism not only to benefit from the fuzzy clustering process but also to get advantage of the multiple membership function of the fuzzy clustering. …”
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Book Section -
16
The new efficient and accurate attribute-oriented clustering algorithms for categorical data
Published 2012“…Many algorithms for clustering categorical data have been proposed, in which attribute-oriented hierarchical divisive clustering algorithm Min-Min Roughness (MMR) has the highest efficiency among these algorithms with low clustering accuracy, conversely, genetic clustering algorithm Genetic-Average Normalized Mutual Information (G-ANMI) has the highest clustering accuracy among these algorithms with low clustering efficiency. …”
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17
Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor
Published 2009“…We ¯nd between 96% and 99.7 % of accuracy in the classi¯cation of 6 di®erent types of Time series by using K-means cluster algorithm and we ¯nd 99.7% by using the new clustering algorithm.…”
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Citation Index Journal -
18
Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor
Published 2008“…We ¯nd between 96% and 99.7 % of accuracy in the classi¯cation of 6 di®erent types of Time series by using K-means cluster algorithm and we ¯nd 99.7% by using the new clustering algorithm.…”
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Citation Index Journal -
19
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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20
Clustering Methods For Cluster-Based Routing Protocols In Wireless Sensor Networks: Comparative Study
Published 2017“…Various approaches of clustering algorithms are used to optimize the energy of routing protocols. …”
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