Search Results - (( java implementation mining algorithm ) OR ( using same clustering algorithm ))
Search alternatives:
- implementation mining »
- java implementation »
- mining algorithm »
- same clustering »
- using same »
-
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. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
2
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. …”
Get full text
Get full text
Thesis -
3
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”. …”
Get full text
Get full text
Get full text
Article -
4
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.…”
Get full text
Get full text
Conference or Workshop Item -
5
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.…”
Get full text
Get full text
Conference or Workshop Item -
6
A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
7
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. …”
Get full text
Get full text
Thesis -
8
Balancing exploration and exploitation in ACS algorithms for data clustering
Published 2019“…The performance of the proposed algorithm is compared with that of several common clustering algorithms using real-world datasets. …”
Get full text
Get full text
Get full text
Article -
9
USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING
Published 2010“…By using similarity measurement of documents‟ characteristic, they can be clustered based on the same category or topic. …”
Get full text
Get full text
Thesis -
10
Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation
Published 2011“…However, two main issues plague these clustering algorithms: initialization sensitivity of cluster centers and unknown number of actual clusters in the given dataset. …”
Get full text
Get full text
Thesis -
11
An Analysis Of Various Algorithms For Text Spam Classification And Clustering Using Rapidminer And Weka
Published 2024“…By using the same dataset, which is downloaded from UCI, Machine Learning Repository, various algorithms used in classification and clustering in this simulation has been analysed comparatively. …”
Article -
12
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). …”
Get full text
Get full text
Get full text
Get full text
Thesis -
13
On density-based data streams clustering algorithms: A survey
Published 2017“…The main idea in these algorithms is using density-based methods in the clustering process and at the same time overcoming the constraints, which are put out by data stream’s nature. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
14
Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
Get full text
Get full text
Article -
15
Cluster optimization in VANET using MFO algorithm and K-Means clustering
Published 2023“…Overall, the MFO Algorithm and K-Means algorithm can be used in combination to optimize the clustering in VANET, leading to better network performance, more reliable communication, and improved efficiency.…”
Get full text
Get full text
Conference or Workshop Item -
16
Feature Selection And Enhanced Krill Herd Algorithm For Text Document Clustering
Published 2018“…Text document (TD) clustering is a new trend in text mining in which the TDs are separated into several coherent clusters, where documents in the same cluster are similar. …”
Get full text
Get full text
Thesis -
17
An enhanced cluster head selection algorithm for routing in mobile AD-HOC network
Published 2017“…This thesis proposes a cluster based routing protocol, the Enhanced Cluster Routing Protocol (ECRP), which uses a modified cluster formation algorithm to build the cluster structure and select one of the nodes to be the cluster head. …”
Get full text
Get full text
Thesis -
18
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…The K-Means algorithm is the commonest and fast technique in partitional cluster algorithms, although with unnormalized datasets it can achieve local optimal. …”
Get full text
Get full text
Get full text
Thesis -
19
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. …”
Get full text
Get full text
Get full text
Article -
20
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The comparison results show that, the clusters labelled by the cluster labelling algorithm were the same as using co-spectral plot. …”
Get full text
Get full text
Thesis
