defaults {ODRF} | R Documentation |
Default values passed to RotMat*
Description
Given the parameter list and the categorical map this function populates the values of the parameter list accoding to our 'best' known general use case parameters.
Usage
defaults(
paramList,
split = "entropy",
dimX = NULL,
weights = NULL,
catLabel = NULL
)
Arguments
paramList |
A list (possibly empty), to be populated with a set of default values to be passed to a |
split |
The criterion used for splitting the variable. 'gini': gini impurity index (classification, default), 'entropy': information gain (classification) or 'mse': mean square error (regression). |
dimX |
An integer denoting the number of columns in the design matrix X. |
weights |
A vector of length same as |
catLabel |
A category labels of class |
Value
Default parameters of the RotMat* function.
-
dimX
An integer denoting the number of columns in the design matrix X. -
dimProj
Number of variables to be projected, defaultdimProj="Rand"
: random from 1 to ncol(X). -
numProj
the number of projection directions.(defaultceiling(sqrt(dimX))
) -
catLabel
A category labels of classlist
in prediction variables, for details see Examples ofODRF
. -
weights
A vector of length same asdata
that are positive weights.(default NULL) -
lambda
Parameter of the Poisson distribution (default 1). -
sparsity
A real number in(0,1)
that specifies the distribution of non-zero elements in the random matrix. Whensparsity
="pois" means that non-zero elements are generated by the p(lambda
) Poisson distribution. -
prob
A probability\in (0,1)
used for sampling from. -
randDist
Parameter of the Poisson distribution (default 1). -
split
The criterion used for splitting the variable. 'gini': gini impurity index (classification, default), 'entropy': information gain (classification) or 'mse': mean square error (regression). -
model
Model for projection pursuit. (seePPO
)
See Also
RotMatPPO
RotMatRand
RotMatRF
RotMatMake
Examples
set.seed(1)
paramList <- list(dimX = 8, numProj = 3, sparsity = 0.25, prob = 0.5)
(paramList <- defaults(paramList, split = "entropy"))