evaluate_best_validation_external_by_metrics {Clustering} | R Documentation |

## Evaluates algorithms by measures of dissimilarity based on a metric.

### Description

Method that calculates which algorithm and which metric behaves best for the datasets provided.

### Usage

```
evaluate_best_validation_external_by_metrics(df, metric)
```

### Arguments

`df` |
Data matrix or data frame with the result of running the clustering algorithm. |

`metric` |
String with the metric. |

### Details

Method groups the data by algorithm and distance measure, instead of obtaining the best attribute from the data set.

### Value

A data.frame with the algorithms classified by measures of dissimilarity.

### Examples

```
result = Clustering::clustering(
df = cluster::agriculture,
min = 4,
max = 5,
algorithm='kmeans_rcpp',
metrics=c("F_measure"))
Clustering::evaluate_best_validation_external_by_metrics(result,'F_measure')
```

[Package

*Clustering*version 1.7.10 Index]