# accuracy: Prediction Accuracy from Stability Assessment Results In stablelearner: Stability Assessment of Statistical Learning Methods

 accuracy R Documentation

## Prediction Accuracy from Stability Assessment Results

### Description

Function to compute the prediction accuracy from an object of class `"stablelearner"` or `"stablelearnerList"` as a parallel to the similarity values estimated by `stability` in each iteration of the stability assessment procedure.

### Usage

``````  accuracy(x, measure = "kappa", na.action = na.exclude,
applyfun = NULL, cores = NULL)
``````

### Arguments

 `x` an object of class `"stablelearner"` or `"stablelearnerList"`. `measure` a character string (or a vector of character strings). Name(s) of the measure(s) used to compute accuracy. Currently implemented measures are `"diag"` = percentage of observations on the main diagonal of a confusion matrix, `"kappa"` = `"diag"` corrected for agreement by chance (default), `"rand"` = Rand index, and `"crand"` = Rand index corrected for agreemend by chance (see also `classAgreement`). `na.action` a function which indicates what should happen to the predictions of the results containing `NAs`. The default function is `na.exclude`. `applyfun` a `lapply`-like function. The default is to use `lapply` unless `cores` is specified in which case `mclapply` is used (for multicore computations on platforms that support these). `cores` integer. The number of cores to use in multicore computations using `mclapply` (see above).

### Details

This function can be used to compute prediction accuracy after the stability was estimated using `stability`.

### Value

A matrix of size `2*B` times length(`measure`) containing prediction accuracy values of the learners trained during the stability assessment procedure.

`stability`

### Examples

``````

library("partykit")
res <- ctree(Species ~ ., data = iris)
stab <- stability(res)
accuracy(stab)

``````

stablelearner documentation built on April 14, 2023, 12:40 a.m.