Performance Charts Creation

Creating a Performance Chart

To create a Performance chart, follow these steps:

Navigate to the Charts tab in your Fiddler AI instance
Click on the Add Chart button on the top right
In the modal, Select the project that has a model with Custom features
Select Performance Analytics

Available Performance charts

Model task	Available Chart(s)
Binary classification	<p>- Confusion Matrix<br>- ROC<br>- Precision Recall<br>- Calibration Plot Charts</p>
Multi-class Classification	- Confusion Matrix
Regression	<p>- Prediction Scatterplot<br>- Error Distribution</p>
Ranking / LLM / Not Set	Not available

Available right side controls

Parameter	Value
Model	List of models in the project
Version	List of versions for the selected model
Environment	`Production` or `Pre-Production`
Dataset	Displayed only if `Pre-Production` is selected. List of pre-production env uploaded for the model version.
Visual	List of possible performance visualization depending on the model task.
Segment	<p>- Selecting a saved segment<br>- Defining an applied (on the fly) segment. This applied segment isn’t saved (unless specifically required by the user) and is applied for analysis purposes.</p>
Max Sample size	<p>Integer representing the maximum number of rows used for computing the chart, up to 500,000. If the data selected has less rows, we will use all the available rows with non null target and output(s).<br>Fiddler select the <code>n</code> first number of rows from the selected slice.<br><br><em>Note: Clickhouse is configured using multiple shards, which means slightly different results can be observed if data is only selected on a specific shard (usually when little observation are queried).</em></p>

Available in-chart controls

Control	Model Task	Value
Time range selection	All	Selecting start time and end time or time label for production data. Default to last 30 days
Positive class threshold	Binary classification	Selecting threshold applied for computation / visualization. Default to 0.5
Displayed labels	Multi-class Classification	Selecting the labels to display on the confusion matrix (up to 12). Default to the 12 first labels

Saving the Chart

Once you’re satisfied with your visualization, you can save the chart. This chart can then be added to a Dashboard. This allows you to revisit the Performance visualization at any time easily either directly going to the Chart or to the dashboard.

Getting Started

Concepts

Evaluate & Test

Reference

Creating a Performance Chart

Available Performance charts

Available right side controls

Available in-chart controls

Saving the Chart

​Creating a Performance Chart

​Available Performance charts

​Available right side controls

​Available in-chart controls

​Saving the Chart

Creating a Performance Chart

Available Performance charts

Available right side controls

Available in-chart controls

Saving the Chart