corral_augmented: Augmented corral data set: synthetic data with correlated...

In sbfc: Selective Bayesian Forest Classifier

Description

This is an artificial domain where the target concept is (X1^X2) V (X3^X4).
Data set from John et al (1994). Training and test splits from SGI.
The first 6 features are the real features from the original corral data set. The rest are noise features added by V. Krakovna by shuffling copies of real features.
The SBFC paper uses subsets of this data set with the first 100 and 1000 features.

Usage

data(corral_augmented)

Format

TrainX

A matrix with 128 rows and 10000 columns.

TrainY

A vector with 128 rows.

References

John et al (1994) paper introducing the corral data set

SBFC paper describing augmentation of corral data set

Examples

corral_result = sbfc(data=list(TrainX=corral_augmented$TrainX[,1:6],
                                         TrainY = corral_augmented$TrainY))
corral100_result = sbfc(data=list(TrainX=corral_augmented$TrainX[,1:100], 
                                  TrainY = corral_augmented$TrainY))

sbfc documentation built on Jan. 16, 2022, 1:06 a.m.