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') plt.ylabel (' Ratio_sugar ') plt.title (' LDA ') plt.show () W=calulate_w () plot (W)The results are as follows: The corresponding W value is:[ -6.62487509e-04, -9.36728168e-01]Because of the relationship between data distribution, LDA's effect is not obvious. So I changed the number of samples of several label=0, rerun the program to get the result as follows:The result is obvious, the corresponding W value is:[-0.60311161,-0.67601433]Transferred from: http://cache.baiducontent.com/c?m= 9d7

Mathematical model, if need to bank loans, according to the loan amount calculation, there are age, wages, assets and other factors, this translates into mathematics is:Now we are to fit a plane to make a diagram, but this fitting theoretical value and the results of the real difference, now we through the statistical error calculation method, we believe that each error is independent of the same distribution, and obey the mean value of 0 variance is the Gauss distribution of the square. Indepen

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