large-volume data sets
Using Very Large Volume Data Sets for Collaborative Systems Study
... of data mining, especially on those commer- cials, which are intended for a single ...for data preprocessing, and for data classification are used decision trees, regression, clusterization, rules ...
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Privacy Preserving Data Analytics using Cryptographic Technique for Large Data Sets
... of data. Nowadays, data has become the centric point of all industry and all are moving around data ...on data value rather than services. Morally, large data volume is ...
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A USE CASE OF BIG DATA EXPLORATION & ANALYSIS WITH HADOOP: STATISTICS REPORT GENERATION
... Big data analytics is the area where advanced analytic techniques operate on big data ...Big data and Analytics and how the two have teamed up to crea te one of the most profound trends in business ...
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Digital tissue and what it may reveal about the brain
... acquiring large volume EM data sets, from the difficulty of uniformly fixing, staining, and embed- ding large pieces of tissue to the challenges of imaging large fields of view ...
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An Efficient Methodology To Sort Large Volume Of Data
... [8]It is the fastest and efficient algorithm for large sets of data. But it is inefficient if the elements in the list are already sorted which results in the worst case time complexity of O(n2). ...
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Projection error evaluation for large multidimensional data sets
... artificial data sets has shown that in order to decrease computation time, the projection error can be evaluated precisely using only representative data sample, but not full data ...the ...
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Systematic Integration of Large Data Sets for Improved Decision-Making
... the data to a temporary volatile memory called the memstore; this is very fast as writing to the memstore is ...enough data has been accumulated in the memstore, the data is then written to HFiles in ...
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A Design Pattern for Efficient Retrieval of Large Data Sets from Remote Data Sources
... Since there is no restriction on how many rows (or objects) a query may return, re- sources must clearly be conserved to cater for the potentially unlimited set of results. Conservation of resources is achieved on the ...
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Training Data Sets Construction from Large Data Set for PCB Character Recognition
... Printed circuits board (PCB) is one of the key concepts in electronics used in different fields of industry. Usually, pattern recognition [1] and computer vision [2] algorithms are used to read and identify characters ...
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Managing Large Data Sets Using Support Vector Machines
... Machine learning is concerned with the development of algorithms which enable the machine to learn and perform tasks. Support vector machines (SVMs) are a set of related supervised learning methods used for ...
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TOWARD A DISTRIBUTED DATA MINING SYSTEM FOR TOURISM INDUSTRY
... of data. Data mining helps businesses sift through layers of seemingly unrelated data for meaningful relationships, where they can anticipate, rather than simply react to, environment ...of ...
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A posteriori correction of camera characteristics from large image data sets
... In one example the average and sigma images from two different datasets, collected on the same camera but almost a year apart, revealed that: some old dust particles remained in the same position on the chip; new “dust” ...
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Using the Amazon Compute Cloud to Analyze Large Data Sets
... • Only allow instances to be passed a single number (the event code) • Nodes only let single number.. through the firewall.[r] ...
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Efficient Streaming Algorithm for Large Volume of Data
... Decision tree is very useful classification and regression technique. Decision Trees are very flexible, easy to understand, and easy to debug. They will work with classification problems and regression problems [19]. So ...
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ObspyDMT: a Python toolbox for retrieving and processing large seismological data sets
... only data that could not be retrieved ...a data center server. All four communicate with data centers via the rel- atively new web services interfaces defined by the ...physical data resources ...
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On Distributed Deep Network for Processing Large-Scale Sets of Complex Data
... Abstract—Recent work in unsupervised feature learning and deep learning has shown that being able to train large models can dramatically improve performance. In this paper, we consider the problem of training a ...
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SeqPig: simple and scalable scripting for large sequencing data sets in Hadoop
... developing data processing pipelines, it is not surprising that a large fraction of computing jobs in contemporary Hadoop deployments originate from Apache Pig or similar high-level tools ...
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Fast automatic classification in extremely large data sets: the RANK approach
... This paper presents VADIS’s built-in RANK solution to cope with very large classification problems. This software embeds and automates many important tasks that must be done to provide a good solution for ...
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Practical Targeted Learning from Large Data Sets by Survey Sampling
... Large data sets are ubiquitous ...from large data ...big data. This is why we use the expression “large data sets” instead of “big ...
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Very Fast Interactive Visualization of Large Sets of High-dimensional Data
... of large high-dimensional data ...high-dimensional data Y, which are sufficient to obtain a proper data embedding in ...each data vector in Y only indices of a small number of the nearest ...
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