# surrogateAssociation

Mean predictive measure of association for surrogate splits in classification tree

## Description

returns a `ma`

= surrogateAssociation(`tree`

)`P`

-by-`P`

matrix, where `P`

is
the number of predictors in `tree`

. `ma(i,j)`

is the
predictive measure of association between the optimal split on variable
`i`

and a surrogate split on variable `j`

. For more
details, see Algorithms.

## Examples

## Input Arguments

## More About

## Algorithms

Element `ma(i,j)`

is the predictive measure
of association averaged over surrogate splits on predictor `j`

for
which predictor `i`

is the optimal split predictor.
This average is computed by summing positive values of the predictive
measure of association over optimal splits on predictor `i`

and
surrogate splits on predictor `j`

and dividing by
the total number of optimal splits on predictor `i`

,
including splits for which the predictive measure of association between
predictors `i`

and `j`

is negative.

## Extended Capabilities

## Version History

**Introduced in R2014b**