Tensor model-based multi-source data classification optimizing method and system
A multi-source data, classification optimization technology, applied in the field of pattern recognition, can solve the problems of low computational efficiency and high computational complexity, and achieve the effect of ensuring high efficiency, improving classification accuracy, and avoiding over-learning
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[0049] 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.
[0050] see figure 1 , is a flow chart of the multi-source data classification and optimization method based on the tensor pattern according to the embodiment of the present invention. The multi-source data classification and optimization method based on the tensor pattern in the embodiment of the present invention includes the following steps:
[0051] Step 100: Introduce multi-view data into a unified tensor product space, and perform tensor product operations on the multi-view data under the Map-reduce distributed framework to obtain high-order tensor data;
[0052] In step 100, Map-Reduce is a...
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