PearsonHeuristic {D2MCS} | R Documentation |
Feature-clustering based on Pearson Correlation Test.
Description
Performs the feature-clustering using Pearson correlation tests. Valid for both, bi-class and multi-class problems.
Details
The test statistic is based on Pearson's product moment correlation coefficient cor(x, y) and follows a t distribution with length(x)-2 degrees of freedom if the samples follow independent normal distributions. If there are at least 4 complete pairs of observation, an asymptotic confidence interval is given based on Fisher's Z transform.
Super class
D2MCS::GenericHeuristic
-> PearsonHeuristic
Methods
Public methods
Method new()
Creates a PearsonHeuristic object.
Usage
PearsonHeuristic$new()
Method heuristic()
Test for association between paired samples using Pearson test.
Usage
PearsonHeuristic$heuristic(col1, col2, column.names = NULL)
Arguments
Returns
A numeric vector of length 1 or NA if an error occurs.
Method clone()
The objects of this class are cloneable with this method.
Usage
PearsonHeuristic$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
See Also
[Package D2MCS version 1.0.1 Index]