View source: R/col_cont_metrics.R

Many metrics for a continuous response variable | R Documentation |

any metrics for a continuous response variable.

```
colmses(y, yhat, parallel = FALSE)
colmaes(y, yhat, parallel = FALSE)
colpkl(y, yhat, parallel = FALSE)
colukl(y, yhat, parallel = FALSE)
```

`y` |
A numerical vector. |

`yhat` |
A numerical matrix with with the predictions. |

`parallel` |
If you want parallel computations set this equal to TRUE. |

The mean squared errors, mean absolute errors, and Kullback-Leibler divergence for percentages (colpkl) and non-negative values or discrete values (colukl) are computed.

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

Michail Tsagris.

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

```
colaccs, bigknn.cv, mmpc, pc.sel
```

```
## 20 variables, hence 20 MSEs will be calculated
y <- rnorm(100, 1, 0.6)
yhat <- matrix( rnorm(100 * 20), ncol = 20 )
a <- colmses(y, yhat)
```

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