I’ll address common interpretations and show how to create deep features from the variance structure of Sxx.
Not exactly. In regression with one independent variable, Sxx refers strictly to the ( x ) variable. SST usually refers to the total sum of squares for ( y ). However, conceptually, they are the same formula applied to different variables. Sxx Variance Formula
Calculating the Sxx variance involves the following steps: I’ll address common interpretations and show how to
For two variables ( x ) and ( y ): [ \textDeepFeature = \frac\textVar(S_xx)\textVar(S_yy) \times \textCov(x,y)^2 ] y)^2 ] For sequential data
For sequential data, apply an LSTM/Transformer to a sequence of ( S_xx ) values and compute the as a meta-feature.