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کامپیوتر و شبکه::
مجموعه داده، مجموعه داده، مجموعه داده
Winshuttle argue if data sets are so large and complex and beyond traditional process and management capability, then these data sets can be considered as Big Data.
Based on this reasoning, we consider that Cox and Ellsworth [10] as proposers of the term Big Data because they assigned a relatively accurate meaning to the existing view of Big Data, which they stated, "...data sets are generally quite large, taxing the capacities of main memory, local disk and even remote disk.
When data sets do not fit in main memory (in core), or when they do not fit even on local disk..."
Their conclusion is that "large-scale data sets of human behavior have the potential to fundamentally transform the way we fight diseases, design cities and perform research."
It does not matter how big the data set is.،To obtain an efficient representation of data geo- metric descriptions, DMs [38] interpreted the eigenfunctions of Markov matrices as a system of coordinates on the original data set.
We first describe three experimental data sets and competitors in Section IV-A.
In Section IV-D, we conduct the experiments on three data sets to demonstrate the benefits of the proposed method for
Data Sets and Competitors
1) Data Sets: To demonstrate the capability of the pro- posed method for HSI DR, three data sets are employed in experiments.،Winshuttle argue if data sets are so large and complex and beyond traditional process and management capability, then these data sets can be considered as Big Data.
Based on this reasoning, we consider that Cox and Ellsworth [10] as proposers of the term Big Data because they assigned a relatively accurate meaning to the existing view of Big Data, which they stated, "...data sets are generally quite large, taxing the capacities of main memory, local disk and even remote disk.
When data sets do not fit in main memory (in core), or when they do not fit even on local disk..."
Their conclusion is that "large-scale data sets of human behavior have the potential to fundamentally transform the way we fight diseases, design cities and perform research."
It does not matter how big the data set is.
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