Clinic pathology data classification method based on combination of principal component analysis and extreme learning machine
A technology of extreme learning machine and principal component analysis, which is applied in neural learning methods, medical data mining, electrical digital data processing, etc., and can solve problems such as high dimensionality, complex calculation, and dimensionality reduction
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[0049] The present invention will be further described below in conjunction with the accompanying drawings.
[0050] refer to figure 1 , a clinical pathological data classification method based on principal component analysis and extreme learning machine combination, described classification method comprises the steps:
[0051] 1) Normalize clinical data, perform feature extraction through principal component analysis, sort feature values according to feature significance, and remove data dimensions below the significance threshold to achieve the purpose of data dimensionality reduction;
[0052] The process of data dimensionality reduction is as follows:
[0053] Suppose there is a set of random samples x 1 , x 2 ,x 3 ,...,x N , x i =[x i1 ,x i2 ,x i3 ,...,x im ] T , i=1,2,...,N, m is the dimension of the sample, and the mean value of this group of samples is marked as
[0054] x ‾ ...
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