Description Usage Arguments Details Value Author(s) See Also Examples

Converting categorical variables into continuous features using the mean of the response variable for the respective categories without using the index record.

1 |

`y` |
Response variable (categorical or continuous). |

`x` |
Predictor variables in the dataframe which are categorical and need to be converted into continuous. |

`data` |
Name of the dataframe. |

`min.obs` |
The minimum number of observations within a category in a categorical variable to get converted into a continuous feature. All the categories which have observations less than the min.obs will form a different category. |

This function is only for categorical variables.

Returns a dataframe with converted features without replacing the original ones.

Santhosh Sasanapuri

1 2 3 4 5 | ```
data(ChickWeight)
# Converting the "Chick" variable into factor from ord.factor for demonstration purposes.
ChickWeight$Chick <- as.factor(as.numeric(ChickWeight$Chick))
# Returns a dataframe with two added columns for "Chick" and "Diet"
head(ctoc(y = "weight", x = c("Chick","Diet"), data = ChickWeight, min.obs = 12))
``` |

```
Loading required package: ggplot2
Loading required package: gplots
Attaching package: 'gplots'
The following object is masked from 'package:stats':
lowess
Loading required package: RColorBrewer
Loading required package: igraph
Attaching package: 'igraph'
The following objects are masked from 'package:stats':
decompose, spectrum
The following object is masked from 'package:base':
union
Diet Chick weight Time Chick_cont Diet_cont
1 1 1 39 0 78.29730 102.9361
2 1 1 35 2 78.40541 102.9543
3 1 10 43 0 90.72727 102.9178
4 1 10 48 2 90.27273 102.8950
5 1 10 55 4 89.63636 102.8630
6 1 10 62 6 89.00000 102.8311
```

corkscrew documentation built on May 29, 2017, 11:24 a.m.

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