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[PDF] Top 20 Parallel K Means Clustering for Gene Expression Data on SNOW

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Parallel K Means Clustering for Gene Expression Data on SNOW

Parallel K Means Clustering for Gene Expression Data on SNOW

... of data, both in terms of size and dimensionality, the sequential K-Means algorithm could face several challenges such as load balancing and ...sequential K-Means for a parallel ... See full document

5

K Means Based Clustering In High Dimensional Data

K Means Based Clustering In High Dimensional Data

... the clustering algorithms cannot create correct results because of the inherent sparsity of the data ...dimensional data does not cluster large ...for clustering high-dimensional ...real-world ... See full document

5

Efficient Clustering for Gene Expression Data

Efficient Clustering for Gene Expression Data

... biological data such as DNA sequences and microarray data have been increased ...the data, explore relationships between genes, understanding severe diseases and development of drugs for patterns ... See full document

6

Aggregation Methodology on Map Reduce for Big Data Applications by using Traffic-Aware Partition Algorithm

Aggregation Methodology on Map Reduce for Big Data Applications by using Traffic-Aware Partition Algorithm

... ABSTRACT: Data clustering is an important data mining technology that plays a crucial role in numerous scientific ...big data as the size of datasets has been growing rapidly to extra- large ... See full document

8

A Comparative Study on K-Means And Genetic Algorithm For Data Clustering

A Comparative Study on K-Means And Genetic Algorithm For Data Clustering

... study K-means & GA techniques are used to find out the support, confidence, memory space and time in seconds of Mushroom, Soyabean and Fishers Iris ...to K-Means algorithm.. ... See full document

9

Review on Optimised Parallel K-Means Clustering using YARN in Hadoop

Review on Optimised Parallel K-Means Clustering using YARN in Hadoop

... big data platform's resource manager and job ...MapReduce's data processing component, enabling Hadoop to support varied types of processing and a broader array of ...streaming data and real-time ... See full document

6

Parallel Clustering of Gene Expression Dataset in Multicore Environment

Parallel Clustering of Gene Expression Dataset in Multicore Environment

... the gene expression dataset. For the clustering process we have proposed the k-means algorithm with better centred ...basic k-means clustering have some drawbacks: ... See full document

6

Modification of the Fast Global K-means Using a Fuzzy Relation with Application in Microarray Data Analysis

Modification of the Fast Global K-means Using a Fuzzy Relation with Application in Microarray Data Analysis

... distinctive expression levels can help in prevention, diagnosis and treatment of the diseases at the genomic ...Global k-means (fast GKM) is developed for clustering the gene ... See full document

10

Classification Connection of Twitter Data using K Means Clustering

Classification Connection of Twitter Data using K Means Clustering

... unnecessary data are whitespaces, stop-words, digits and various emoticon ...the data and gradually reduces the error percentage with each iteration in the ...The clustering would occur such that ... See full document

9

CLASSIFICATION BY K MEANS CLUSTERING

CLASSIFICATION BY K MEANS CLUSTERING

... given data set through a certain number of clusters (assume k clusters) fixed a ...define k centroids, one for each ...given data set and associate it to the nearest ...re-calculate k ... See full document

5

Performance of Students Evaluation in Education Sector Using Clustering K-Means Algorithms

Performance of Students Evaluation in Education Sector Using Clustering K-Means Algorithms

... unknown data, various methods and techniques were used such as the Association rules, pattern mining, classification technique, clustering technique, prediction, Supervised and unsupervised learning ... See full document

6

Formation of K-Means and Density Based Clustering In Data Mining

Formation of K-Means and Density Based Clustering In Data Mining

... different data objects are grouped into various data sets ...other. K-means clustering is a kind of unsupervised learning; it is utilized unlabeled information (information without ... See full document

7

Crime Data Analysis in Python using K   Means Clustering

Crime Data Analysis in Python using K Means Clustering

... K-means clustering make use of unsupervised learning to solve the known ...A Kmeans algorithm can be applied to a numerical and continous data with minimal ... See full document

5

Clustering of Mixed Data Types with Application to Toxicogenomics

Clustering of Mixed Data Types with Application to Toxicogenomics

... the data was to a) identify biomarkers related to histopathological changes following exposure to a toxicant or b) ascertain biological processes and pathways related to the histopathology ...for data ... See full document

233

International Journal of Computer Science and Mobile Computing

International Journal of Computer Science and Mobile Computing

... WEKA has its full form- Waikato Environment for Knowledge Learning, [7] which is an open source tool meaning available at public use. Developed at the University of Waikato in New Zealand, WEKA is a computer program ... See full document

15

Clustering for binary data sets by using genetic algorithm incremental K means

Clustering for binary data sets by using genetic algorithm incremental K means

... of K-means to cluster large data sets, several researchers have proposed an Incremental K-means ...of data. However, IKM still facing some problem when dealing with larger ... See full document

6

A State of Art Analysis of Telecommunication Data by k Means and k Medoids Clustering Algorithms

A State of Art Analysis of Telecommunication Data by k Means and k Medoids Clustering Algorithms

... major data analysis methods widely used for many practical applications in emerging areas of data ...similarity. Clustering techniques are applied in different domains to predict future trends of ... See full document

13

K means Clustering Algorithm Based on E Commerce Big Data

K means Clustering Algorithm Based on E Commerce Big Data

... The clustering comes under unsupervised learning process as the clusters of similar objects form automatically. We can cluster anything, and the better our clusters are, the more similar items are in the cluster. ... See full document

5

DOCUMENT CLUSTERING USING HADOOPS MAP REDUCE OPERATION Mr. Vitthal Kumbhar *1 , Dr. Shyamrao Gumaste 2

DOCUMENT CLUSTERING USING HADOOPS MAP REDUCE OPERATION Mr. Vitthal Kumbhar *1 , Dr. Shyamrao Gumaste 2

... mines data efficiently by using traditional relational database management ...system. Data used by existing application is in structured ...handle data which is in unstructured ...for ... See full document

7

Medical Image Segmentation using Modified K Means Clustering

Medical Image Segmentation using Modified K Means Clustering

... modified k means clustering is ...C-Means Clustering, K-Means Clustering with Modified K- Means Clustering is performed then the performance ... See full document

5

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