View source: R/col_binary_metrics.R

Many binary classification metrics | R Documentation |

Many binary classification metrics.

```
colaccs(group, preds)
colsens(group, preds)
colspecs(group, preds)
colprecs(group, preds)
colfscores(group, preds)
colfbscores(group, preds, b)
colfmis(group, preds)
```

`group` |
A numerical vector with two values, 0 and 1. |

`preds` |
A numerical matrix with scores, probabilities or any other measure. |

`b` |
The |

The accuracies, sensitivities, specificities, precisions, F-scores, `F_{\beta}`

-scores
and the Fowlkes-Mallows index are calculated column-wise. The colaccs is the
only metric that can be used with a multinomial response as well.

A vector with length equal to the number of columns of the "preds" argument containing the relevant values computed for each column.

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.

https://en.wikipedia.org/wiki/Sensitivity_and_specificity

https://en.wikipedia.org/wiki/Precision_and_recall

```
colmses, bernoulli.nb, bigknn.cv
```

```
## 20 variables, hence 20 accuracies will be calculated
ina <- rbinom(100, 1, 0.6)
x <- matrix( rnorm(100 * 20), ncol = 20 )
a <- colaccs(ina, x)
```

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