Use batch testing to find prediction accuracy issues

This tutorial demonstrates how to use batch testing to find utterance prediction issues.

In this tutorial, you learn how to:

  • Create a batch test file
  • Run a batch test
  • Review test results
  • Fix errors for intents
  • Retest the batch


  • For this article, you also need a LUIS account in order to author your LUIS application.


If you do not already have a subscription, you can register for a free account.

Create new app

This article uses the prebuilt domain HomeAutomation. The prebuilt domain has intents, entities, and utterances for controlling HomeAutomation devices such as lights. Create the app, add the domain, train, and publish.

  1. In the LUIS website, create a new app by selecting Create new app on the MyApps page.

    Create new app

  2. Enter the name Batchtest-HomeAutomation in the dialog.

    Enter app name

  3. Select Prebuilt Domains in bottom left corner.

    Select Prebuilt Domain

  4. Select Add Domain for HomeAutomation.

    Add HomeAutomation domain

  5. Select Train in the top right navigation bar.

    Select Train button

Batch test criteria

Batch testing can test up to 1000 utterances at a time. The batch should not have duplicates. Export the app in order to see the list of current utterances.

The test strategy for LUIS uses three separate sets of data: model utterances, batch test utterances, and endpoint utterances. For this tutorial, make sure you are not using the utterances from either model utterances (added to an intent), or endpoint utterances.

Do not use any of the utterances already in the app for the batch test:

'breezeway on please',
'change temperature to seventy two degrees',
'coffee bar on please',
'decrease temperature for me please',
'dim kitchen lights to 25 .',
'fish pond off please',
'fish pond on please',
'illuminate please',
'living room lamp on please',
'living room lamps off please',
'lock the doors for me please',
'lower your volume',
'make camera 1 off please',
'make some coffee',
'play dvd',
'set lights bright',
'set lights concentrate',
'set lights out bedroom',
'shut down my work computer',
'silence the phone',
'snap switch fan fifty percent',
'start master bedroom light .',
'theater on please',
'turn dimmer off',
'turn off ac please',
'turn off foyer lights',
'turn off living room light',
'turn off staircase',
'turn off venice lamp',
'turn on bathroom heater',
'turn on external speaker',
'turn on my bedroom lights .',
'turn on the furnace room lights',
'turn on the internet in my bedroom please',
'turn on thermostat please',
'turn the fan to high',
'turn thermostat on 70 .' 

Create a batch to test intent prediction accuracy

  1. Create homeauto-batch-1.json in a text editor such as VSCode.

  2. Add utterances with the Intent you want predicted in the test. For this tutorial, to make it simple, take utterances in the HomeAutomation.TurnOn and HomeAutomation.TurnOff and switch the on and off text in the utterances. For the None intent, add a couple of utterances that are not part of the domain (subject) area.

    In order to understand how the batch test results correlate to the batch JSON, add only six intents.

          "text": "lobby on please",
          "intent": "HomeAutomation.TurnOn",
          "entities": []
          "text": "change temperature to seventy one degrees",
          "intent": "HomeAutomation.TurnOn",
          "entities": []
          "text": "where is my pizza",
          "intent": "None",
          "entities": []
          "text": "help",
          "intent": "None",
          "entities": []
          "text": "breezeway off please",
          "intent": "HomeAutomation.TurnOff",
          "entities": []
          "text": "coffee bar off please",
          "intent": "HomeAutomation.TurnOff",
          "entities": []

Run the batch

  1. Select Test in the top navigation bar.

    Select Test in navigation bar

  2. Select Batch testing panel in the right-side panel.

    Select Batch test panel

  3. Select Import dataset.

    Select Import dataset

  4. Choose the file system location of the homeauto-batch-1.json file.

  5. Name the dataset set 1.

    Select file

  6. Select the Run button. Wait until the test is done.

    Select Run

  7. Select See results.

    See results

  8. Review results in the graph and legend.

    Batch results

Review batch results

The batch results are in two sections. The top section contains the graph and the legend. The bottom section displays utterances when you select an area name of the graph.

Any errors are indicated by the color red. The graph is in four sections, with two of the sections displayed in red. These are the sections to focus on.

The top right section indicates the test incorrectly predicted the existence of an intent or entity. The bottom left section indicates the test incorrectly predicted the absence of an intent or entity.

HomeAutomation.TurnOff test results

In the legend, select the HomeAutomation.TurnOff intent. It has a green success icon to the left of the name in the legend. There are no errors for this intent.

Batch results

HomeAutomation.TurnOn and None intents have errors

The other two intents have errors, meaning the test predictions didn't match the batch file expectations. Select the None intent in the legend to review the first error.

None intent

Failures appear on the chart in the red sections: False Positive and False Negative. Select the False Negative section name in the chart to see the failed utterances below the chart.

False negative failures

The failing utterance, help was expected as a None intent but the test predicted HomeAutomation.TurnOn intent.

There are two failures, one in HomeAutomation.TurnOn, and one in None. Both were caused by the utterance help because it failed to meet the expectation in None and it was an unexpected match for the HomeAutomation.TurnOn intent.

To determine why the None utterances are failing, review the utterances currently in None.

Review None intent's utterances

  1. Close the Test panel by selecting the Test button on the top navigation bar.

  2. Select Build from the top navigation panel.

  3. Select None intent from list of intents.

  4. Select Control+E to see the token view of the utterances

    None intent's utterances Prediction score
    "decrease temperature for me please" 0.44
    "dim kitchen lights to 25." 0.43
    "lower your volume" 0.46
    "turn on the internet in my bedroom please" 0.28

Fix None intent's utterances

Any utterances in None are supposed to be outside of the app domain. These utterances are relative to HomeAutomation, so they are in the wrong intent.

LUIS also gives the utterances less than 50% (<.50) prediction score. If you look at the utterances in the other two intents, you see much higher prediction scores. When LUIS has low scores for example utterances, that is a good indication the utterances are confusing to LUIS between the current intent and other intents.

To fix the app, the utterances currently in the None intent need to be moved into the correct intent and the None intent needs new, appropriate intents.

Three of the utterances in the None intent are meant to lower the automation device settings. They use words such as dim, lower, or decrease. The fourth utterance asks to turn on the internet. Since all four utterances are about turning on or changing the degree of power to a device, they should be moved to the HomeAutomation.TurnOn intent.

This is just one solution. You could also create a new intent of ChangeSetting and move the utterances using dim, lower, and decrease into that new intent.

Fix the app based on batch results

Move the four utterances to the HomeAutomation.TurnOn intent.

  1. Select the checkbox above the utterance list so all utterances are selected.

  2. In the Reassign intent drop-down, select HomeAutomation.TurnOn.

    Move utterances

    After the four utterances are reassigned, the utterance list for the None intent is empty.

  3. Add four new intents for the None intent:


    These utterances are definitely outside the domain of HomeAutomation. As you enter each utterance, watch the score for it. The score may be low, or even very low (with a red box around it). After you train the app, in step 8, the score will be much higher.

  4. Remove any labels by selecting the blue label in the utterance and select Remove label.

  5. Select Train in the top right navigation bar. The score of each utterance is much higher. All scores for the None intent should be above .80 now.

Verify the fix worked

In order to verify that the utterances in the batch test are correctly predicted for the None intent, run the batch test again.

  1. Select Test in the top navigation bar.

  2. Select Batch testing panel in the right-side panel.

  3. Select the three dots (...) to the right of the batch name and select Run Dataset. Wait until the batch test is done.

    Run dataset

  4. Select See results. The intents should all have green icons to the left of the intent names. With the right filter set to the HomeAutomation.Turnoff intent, select the green dot in the top right panel closest to the middle of the chart. The name of the utterance appears in the table below the chart. The score of breezeway off please is very low. An optional activity is to add more utterances to the intent to increase this score.

    Run dataset

Next steps