Validating articles

Validation errors are user-friendly and, unlike the bold red error message, pleasing to the eye.

Best of all, validation errors respond directly to your user’s input.

In this section, we describe the most widely used clustering validation indices.

validating articles-36validating articles-79

Look at the within.(within clusters sum of squares), the average.within (average distance within clusters) and silwidths (vector of cluster average silhouette widths).

Among the values returned by the function cluster.stats(), there are two indexes to assess the similarity of two clustering, namely the corrected Rand index and Meila’s VI.

These internal measure can be used also to determine the optimal number of clusters in the data.

The silhouette analysis measures how well an observation is clustered and it estimates the average distance between clusters.

Once you create a validation test, you can style its output with CSS (just as you can style any element in the Shiny user-interface).

Validation errors are HTML div objects with the class If you have questions about this article or would like to discuss ideas presented here, please post on RStudio Community.

This code contains three conditions that fail and one that passes: in a way that might frustrate your user.

A user may not enjoy fixing one validation error to find another (and then another) take its place.

We know that the iris data contains exactly 3 groups of species.

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