Running Time Analysis of Large Data Sets
Time series clustering in large data sets
... a large time series ...recordings. Time series (feature vectors) are produced from these clips using a simplistic signal processing ...a time series dimensionality together with the number of ...
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Time and Streak Surfaces for Flow Visualization in Large Time-Varying Data Sets
... of time and streak surface computation over stream and path surfaces can be traced back to two main factors: first, many more particles are required for adequate discretization, and second, instead of an advancing ...
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Integrative analysis of large-scale biological data sets
... New analysis types like network-based topology analysis and co- expression analysis complement existing tools • For further details: See our publications in BMC Bioinformatics (Glaab et ...
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Computing with large data sets
... What system memory do we need to cluster 500,000 genetic changes mesured for 20,000 individuals? Assuming there are many fewer classes / clusters / model-components than observations we can use a block aproach , where a ...
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Analysis of large data sets using formal concept lattices
... Although large data sets may be difficult to deal with computationally, it is the number of formal concepts derived from a data set that is the key factor in de- termining if a concept lattice ...
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Analysis and Performance Evaluation of Large Data Sets Using Hadoop
... very large data reliably, and to stream those data at very high bandwidth to user ...a large cluster of Commodity machines. Here the immense of data is loaded in HDFS for data ...
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Strategies for MCR image analysis of large hyperspectral data sets
... image data, 256 256 pixels, over an area of 500 500 m m were acquired from each spot which was subsequently collated for analysis as a single ...PCA analysis of this data-set ...image ...
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CULTURAL ANALYTICS: ANALYSIS AND VISUALIZATION OF LARGE CULTURAL DATA SETS
... first time can be visualized as a dynamic process in sufficient ...enough data sources to drive such visualizations, therefore is simply a matter ...
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Strategies for MCR image analysis of large hyperspectral data-sets
... Keywords: time-of-flight secondary ion mass spectrometry; multivariate curve resolution; microarray; high-performance computing Introduction Many applications of materials in biomedicine suffer from sub- optimal ...
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HistogramTools for Distributions of Large Data Sets
... a large MapReduce environment, and need to merge histograms from subsets of the data to obtain a histogram for the whole data ...store large numbers of histograms generated frequently by ...
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Applicability of MAHOUT for Large Data Sets
... of data mining awareness can lead to unpredictable ...box”. Large directories and source files detract from Mahout’s ...given data set and ...enough analysis to encourage the possibilities of ...
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WITH the availability of large data sets in application
... of large data sets in application areas like bioinformatics, medical informatics, scien- tific data analysis, financial analysis, telecommunications, retailing, and marketing, it ...
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Exploratory analysis of large spatial time series and network interaction data sets: house prices in England and Wales
... Such data covers a range of both space and time, and the techniques for visualis ing data th at extends into both space and time are surprisingly limited, despite the early suggestion by ...
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Analysis of large time-series data in OpenTSDB
... performance analysis, green line is for batch size 1, red line is for batch size 100 and blue line is for batch size ...vs time, x-axis denote different size of scan cache used during this experiment and ...
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Practical algorithms for clustering and modeling large data sets : analysis and improvements
... The SEM algorithm is even simpler than the MCEM algorithm. In- stead of maximizing the expectation as done in the second step of the EM algorithm, it uses the distribution from the first step to simply guess the missing ...
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Fractal Analysis of Time-Series Data Sets: Methods and Challenges
... coarse-scale analysis cutoff generally corresponds to a limit of the range of length scales measured, which in turn gener- ally is related to the coarse-scale size of the structure ...
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4 Techniques for Analyzing Large Data Sets
... Larger sectors are more likely to identify areas of conflict, and it is less likely that better solutions will be missed, because they would require that some taxon be moved outside the sector being analyzed. After ...
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Mining for empty spaces in large data sets
... staircase, which as stated is O(d n d−2 ). Doing this for every 0-entry x; y; z requires a total of O(N 0 d n d−2 ) time. When constructing staircase(x; y; z) from staircase(x − 1; y; z) some new stairs are ...
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An Agglomerative Clustering Method for Large Data Sets
... In Data Mining, agglomerative clustering algorithms are widely used because their flexibility and conceptual ...on large data sets, and could also be used as a linear time ...
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SEARCHING LARGE DATA SETS IN GRID COMPUTING
... configuring, running, interacting, securing, optimizing, and curative themselves with least person interference, and has direct to a number of current explore initiative such as , Cognitive Grids ,Autonomic Grids, ...
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