Zero Mean Normalization
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Zero-mean normalization is also called Z-score normalization. The values of attribute X are normalized using the mean and standard deviation of X. A new value new_v is obtained using the following expression:
In such a case, we can substitute Ux1 for Ux and Sx1 for Sx in the expression above.
After zero-mean normalizing each feature will have a mean value of 0.
Also, the unit of each value will be the number of (estimated) standard deviations away from the (estimated) mean.
Note that z-score normalization may be sensitive to small values of Sx.
When zero-mean normalization is applied, all the data in each profile are slid vertically so that their average is zero:
The blue profile was obtained from the red one by a vertical translation so that the average of the profile be zero.
From:http://blog.163.com/penansord@126/blog/static/74642408200931541934535/
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