# [R] Is there a function for this?

Gabor Grothendieck ggrothendieck at gmail.com
Wed Jan 3 16:24:02 CET 2007

```Try this:

> table(actual, pred)
pred
good   1    3

> prop.table(table(actual, pred), 1)
pred
good 0.25 0.75

> prop.table(table(actual, pred), 2)
pred
good 0.25 0.75

> library(gmodels)
> CrossTable(actual, pred)

Cell Contents
|-------------------------|
|                       N |
| Chi-square contribution |
|           N / Row Total |
|           N / Col Total |
|         N / Table Total |
|-------------------------|

Total Observations in Table:  8

| pred
actual |       bad |      good | Row Total |
-------------|-----------|-----------|-----------|
bad |         3 |         1 |         4 |
|     0.500 |     0.500 |           |
|     0.750 |     0.250 |     0.500 |
|     0.750 |     0.250 |           |
|     0.375 |     0.125 |           |
-------------|-----------|-----------|-----------|
good |         1 |         3 |         4 |
|     0.500 |     0.500 |           |
|     0.250 |     0.750 |     0.500 |
|     0.250 |     0.750 |           |
|     0.125 |     0.375 |           |
-------------|-----------|-----------|-----------|
Column Total |         4 |         4 |         8 |
|     0.500 |     0.500 |           |
-------------|-----------|-----------|-----------|

On 1/3/07, Feng Qiu <hustqiufeng at sohu.com> wrote:
> Hi everybody, I'm trying to do a statistic on the error rate of a prediction
> algorithm.
>
> suppose this is the real category
> this is the predicted category
>
> I'm trying to do a statistic on the error rate for each group("good","bad"):
> what percentage of instances are predicted incorrectly for each group ?
> Of course I can write a loop to do that, but is there a easy way to do that?
>
> Thank you!
>
> Best,
>
> Feng
>

```