# predictPairProb: Predict the probability that row1 has a higher criterion than... In heuristica: Heuristics Including Take the Best and Unit-Weight Linear

## Description

Given two rows and a fitted heuristic, returns the heuristic's predicted probability that row1's criterion will be greater than row2's.

## Usage

 `1` ```predictPairProb(row1, row2, object) ```

## Arguments

 `row1` The first row of cues (will apply cols_to_fit for you, based on object). `row2` The second row (will apply cols_to_fit for you, based on object). `object` The fitted heuristic, e.g. a fitted ttbModel or logRegModel. (More technically, it's any object that implements predictProbInternal.)

## Value

A double from 0 to 1, representing the probability that row1's criterion is greater than row2's criterion. 0.5 could be a guess or tie.

`rowPairApply` to get predictions for all row pairs of a matrix or data.frame.
 ```1 2 3``` ```train_matrix <- cbind(y=c(5,4), x1=c(1,0), x2=c(0,1)) lreg <- logRegModel(train_matrix, 1, c(2,3)) predictPairProb(oneRow(train_matrix, 1), oneRow(train_matrix, 2), lreg) ```