plot1SDRule {bestglm} | R Documentation |

## Plot Regularization Path and One Standard Deviation Rule

### Description

Takes input either matrix with 2 columns or output from caret::train() and produces a plot showing the best model selected using the 1 SD rule.

### Usage

```
plot1SDRule(ans, main = "", sub = "", xlab = "df", ylab = "EPE")
```

### Arguments

`ans` |
matrix or output from train |

`main` |
optional plot title |

`sub` |
optional plot subtitle |

`xlab` |
optional x-axis label |

`ylab` |
optional y-axis label |

### Value

tuning parameter value for best model

### Author(s)

A. I. McLeod

### References

Hastie, Tibsharani and Friedman, "Elements of Statistical Learning".

### See Also

### Examples

```
CV<-c(1.4637799,0.7036285,0.6242480,0.6069406,0.6006877,0.6005472,0.5707958,
0.5907897,0.5895489)
CVsd<-c(0.24878992,0.14160499,0.08714908,0.11376041,0.08522291,
0.11897327,0.07960879,0.09235052,0.12860983)
CVout <- matrix(c(CV,CVsd), ncol=2)
oneSDRule(CVout)
```

[Package

*bestglm*version 0.37.3 Index]