Description Usage Arguments Value References
Draws a Stability plot for CMB.
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D |
Data matrix. Has to be an n \times (p+1)-dimensional data frame in the format (X,Y). The X-part must not contain an intercept column containing only ones since this column will be added automatically. |
nsing |
Number of observations (rows) used for the SingBoost submodels. |
Bsing |
Number of subsamples based on which the SingBoost models are validated. Default is 1. Not to confuse with parameter |
alpha |
Optional real number in ]0,1]. Defines the fraction of best SingBoost models used in the aggregation step. Default is 1 (use all models). |
singfam |
A SingBoost family. The SingBoost models are trained based on the corresponding loss function. Default is |
evalfam |
A SingBoost family. The SingBoost models are validated according to the corresponding loss function. Default is |
sing |
If |
Mseq |
A vector of different values for M. |
m_iter |
Number of SingBoost iterations. Default is 100. |
kap |
Learning rate (step size). Must be a real number in ]0,1]. Default is 0.1 It is recommended to use a value smaller than 0.5. |
LS |
If a |
best |
Needed in the case of localized ranking. The parameter |
wagg |
Type of row weight aggregation. |
robagg |
Optional. If setting |
lower |
Optional argument. Only reasonable when setting |
B |
Number of subsamples of size n_{cmb} of the training data for CMB aggregation. |
ncmb |
Number of samples used for |
... |
Optional further arguments |
relev |
List of relevant variables (represented as their column number). |
ind |
Vector of relevant variables (represented as their column number). |
Werner, T., Gradient-Free Gradient Boosting, PhD Thesis, Carl von Ossietzky University Oldenburg, 2020
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