Dimension reduction and correlation analysis method suitable for large-scale data
A large-scale data and association analysis technology, applied in the fields of computer science and image processing, can solve the problems of insufficient utilization of speed and memory efficiency, and achieve the effect of improving computing speed and memory utilization, and using memory efficiently
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[0036] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0037] Such as figure 1 A dimensionality reduction and association analysis method suitable for large-scale data is shown, including the following steps:
[0038] Step 1, data initialization, collect data sample set X(M 1 ×N) and Y(M 2 ×N) as the required data set. Explain M here 1and M 2 Indicate the dimensions of data sets X and Y respectively, that is, each row of X and Y is an attribute of the data; X=[x 1 x 2 ... x N ], similarly, Y=[y 1 the y 2 ... y N ], N represents the number of samples of the data, that is, each column of vectors (ie x i and y i , i=1, 2,...N) represent al...
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