Electron microscopy
  
Variance of Input Data for ML
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A formula, which can be used to calculate the variance () of a set of values for i = 1, 2, … , , can be,

          variance ------------------------------ [3716a]

where,

is the number of data points.

The variance is a measure of how spread out the values in a dataset are. It's the average of the squared differences from the mean.

Figure 3716 shows the data distribution, KDE (kernel density estimation) and variance before and after normalization.

Before normalization
After normalization
Data distribution
Data distribution
(a)
Data distribution
Data distribution
(b)
Data distribution
Data distribution
(c)
Figure 3716. (a) Data distribution, (b) KDE (kernel density estimation), and (c) Variance before and after normalization ( Code).

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