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On this page
  • Creating a Performance Chart
  • Available Performance charts
  • Available right side controls
  • Available in-chart controls
  • Saving the Chart

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  1. Product Guide
  2. Enhance Model Insights with Fiddler's Slice and Explain

Performance Charts Creation

PreviousMetric Card CreationNextPerformance Charts Visualization

Last updated 3 months ago

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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

- Confusion Matrix - ROC - Precision Recall - Calibration Plot Charts

Multi-class Classification

- Confusion Matrix

Regression

- Prediction Scatterplot - Error Distribution

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

Segment

- Selecting a saved segment - 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.

Max Sample size

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). Fiddler select the n first number of rows from the selected slice. 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).

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.

List of possible depending on the model task.

performance visualization

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