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Update the metrics visualization content #1156

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merged 1 commit into from Dec 13, 2020
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Update the metrics visualization content #1156

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4 changes: 3 additions & 1 deletion docs/source/recipes/visualizing-output-in-the-kfp-ui.md
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Expand Up @@ -20,6 +20,8 @@ limitations under the License.

Pipelines that you run on Kubeflow Pipelines can optionally produce output that is rendered in the Kubeflow Pipelines UI. For example, a model training script might expose quality metrics.

You can try the visualizations shown in this document using [this pipeline in the Elyra examples repository](https://github.com/elyra-ai/examples/tree/master/pipelines/visualize_output_in_kubeflow_pipelines_ui).

## Visualizing output using the Kubeflow Pipelines output viewer

The output viewer in the Kubeflow Pipelines UI can render output such as a confusion matrix, ROC curve, or markdown, that is displayed in the Kubeflow Pipelines UI.
Expand All @@ -43,7 +45,7 @@ matrix = [

df = pd.DataFrame(matrix,columns=['target','predicted','count'])

metrics = {
metadata = {
"outputs": [
{
"type": "confusion_matrix",
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