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However, since the results of cross-validation were used in model optimization (i.e. selecting scaling weight for cross-terms and number of extracted PLS components) there is a risk for a bias in the Q2 estimate, and we wanted to ascertain that these high Q2 values were not overoptimistic.
For the DREM 2.0 analysis the following options were not set to default values: (i) genes in the time course were discarded if "Minimum Absolute Expression Change" was smaller than 0.5, (ii) "incorporate expression in regulator data" was activated for transcription factors with "Expression scaling weight" set to 1.
Mathematically, this scaling weight
The inverse standard deviation is used as a scaling weight for each MR-measure.
The Pareto algorithm calculates for each variable the standard deviation s k (standard deviation of the k variable), and the scaling weight is obtained as the inverse of standard deviation root W = 1 / s k.
Similar(55)
Similarly to scaling, weighting is not sensitive to small deviations in the values of the weighting parameters.
The questions and scaling weights used to create the scale can be found in Guo et al. [55].
First, a best practice for scaling weights across multiple levels has yet to be advanced.
Unit variance scaling weights each of the variables by the variable's group standard deviation and therefore does not bias models towards large concentration metabolites.
(a) The degree distribution and (b) the weight distribution for different aggregation intervals, (c) the scaled degree distribution and (d) the scaled weight distribution.
The relevant scaled weight for use with the deregressed information on this individual assuming c = 0.5 can be found using (10) as.
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