large data set
An Advanced Clustering Algorithm (ACA) for Clustering Large Data Set to Achieve High Dimensionality
... in data mining; this method of clustering algorithm will manipulate the clustering results ...and large data set ...each data object to the cluster recursively and save the execution ...
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A Efficient Pruninng Approach to Discover Interesting Pattern Form Large Data Set
... Mining Expected Utility Two Phase and several other algorithms have mine high utility item set very efficiently. But there is need to enhance this algorithm so that it can be applied to large sized dataset. ...
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Efficient Spectral Clustering for Large Data Set Mr B Subba Reddy & Mr K Arun Bhaskar
... for large data sets, we proposed a principled and flexible framework for constrained spectral clustering that can incorporate large amounts of both hard and soft ...side data, it can acquire ...
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Performance Tuning and Scheduling of Large Data Set Analysis in Map Reduce Paradigm by Optimal Configuration using Hadoop
... of data to be processed over very large ...for large data ...very large data sets is performed using the MapReduce ...hold data in the cloud environment due to its ...
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An Efficient Modified K-Means Algorithm To Cluster Large Data-set In Data Mining
... The K-mean algorithm is a popular clustering algorithm and has its application in data mining ,image segmentation, bioinformatics and many other fields[14].This algorithm works well with small datasets.In this ...
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Training Data Sets Construction from Large Data Set for PCB Character Recognition
... of data in the large dataset [6] by using a grid-based algorithm which reduces a dataset by keeping its original data ...a large size of the dataset, we can use these data reduction ...
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Mining geriatric assessment data for in-patient fall prediction models and high-risk subgroups
... a large data set using data mining methods can compete with current dedicated fall risk screening tools, yet lack diagnostic ...assessment data, especially when combined with domain ...
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Mixed effect models for predicting microbial interactions in the vaginal ecosystem
... A large data set was assembled from in vivo studies describing the healthy vaginal environment, and the data set was analyzed to determine whether statistical models which would accurate[r] ...
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Incorporation of gene-specific variability improves expression analysis using high-density DNA microarrays
... extraordinarily large data ...U95A-E set, the basis and principles underlying our analysis are applicable to any oligonucle- otide ...probe set-specific variability exists, but also offer the ...
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A Survey on Hadoop Storage Issues Reetesh Rai, Shravan Kumar
... are data intensive in nature. As huge volumes of the data are generated day by day, more number of popular applications becomes data-intensive in ...the data mining and web indexing ...
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A large-scale crop protection bioassay data set
... for data analysis 42 ...although data are extracted manually and further curated, some errors are inevitable in such a large data set and therefore data should always be treated ...
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Active learning methods for classification and regression problems
... for large data applications. Their strategy queries for a set of samples according to a distribution as determined by the current separating hyperplane and an adaptive confidence ...training ...
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Error, reproducibility and sensitivity : a pipeline for data processing of Agilent oligonucleotide expression arrays
... of data preprocessing for this platform. Using a set of data generated from this array platform, we dissect the major contributors to experimental variability within the ...extract data from ...
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Power and false positive rates for the restricted partition method (RPM) in a large candidate gene data set
... The first point suggested by these data relates to including genotyped relatives in an analysis designed for unrelated individuals. It is often argued that the conservative approach is to select one subject per ...
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Anomaly behaviour detection based on the meta-Morisita index for large scale spatio-temporal data set
... spatio-temporal data remains a rapidly growing prob- lem in the wake of an ever-increasing number of advanced sensors that are continu- ously generating large-scale ...cyber data carries with it an ...
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Big data analytics vs Data Mining analytics
... Big data is collection of complex, large varieties of data set – structured, unstructured and semi structured data that is arriving continuously at high velocity and have capability for ...
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Subgraph Matching with Set Similarity in a Large Graph Database
... A cross section situated document looking software for knowledge, which makes use of SPARQL for knowledge shopping. In addition this know-how is used to acquire field linkage between searching keyword, in order that RDF ...
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ONTOLOGY MATCHING: IN SEARCH OF CHALLENGES AHEAD
... big data and its practice. There is no disbelief that the big data uprising has ...big data propose favorable business paybacks, there are substantial privacy ...for data privacy ...big ...
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IJCSMC, Vol. 3, Issue. 3, March 2014, pg.562 – 568 RESEARCH ARTICLE A Comparative Study on Performance Evalution of Eager versus Lazy Learning Methods
... Abstract: - Classification is one of the fundamental tasks in data mining and has also been studied extensively in statistics, machine learning, neural networks and expert systems over decades. Naïve Bayes, ...
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A large, consistent plasma proteomics data set from prospectively collected breast cancer patient and healthy volunteer samples
... employed data dependent LC-MS/MS approach, presents several ...of data in the mass spectrometer since the duty cycle of the instrument is not occupied with collecting the second MS information during pro- ...
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