Inspect Model Inputs
Read BigML model [model ID]. Summarize the returned field definitions and identify the inputs needed for my prediction data.
Leina connects to BigML to help you run supplied data through an existing prediction model. Ask in your team chat. Leina does the work and brings back the result.
Connect BigML, choose what to share, and hand off your first task.
You
Use our BigML renewal model [model ID] for two accounts. Set months_active to 18 and weekly_sessions to 12 for Cedar; use 3 and 1 for Brook. Compare their predicted outcomes when processing finishes.
Leina
Both predictions have finished. The model returned “renew” for Cedar and “not renew” for Brook.
BigML · Completed predictions
Two account renewal predictions
Results from the selected renewal model.
AI submits your field values to a selected BigML model, checks the prediction’s processing status, and explains the returned output once it finishes.
You specify the source and the destination. Leina uses the content available to your connection and returns the result for you to review.
BigML is a machine learning platform for building models and using them to make predictions from structured data.
Supply the model ID and input values using its field names or identifiers.
AI creates the predictions and retrieves their outputs after processing completes.
Copy a prompt, add your details, and send it to Leina in your connected team chat.
Read BigML model [model ID]. Summarize the returned field definitions and identify the inputs needed for my prediction data.
For BigML model [model ID], create a prediction using input data [JSON object matching model fields]. Retrieve it by the returned prediction ID until its status is complete or an error is reported, then summarize the returned prediction.
Your next BigML task can start with a message.
Tell Leina what you need in your team chat. Include the source, destination, and expected result.
Connect the tools involved and give Leina access to the content it needs.
Share the source material, say where the result belongs, and describe what you need.
Review the result and any changes in the connected app.
Hand off these everyday tasks to your AI employee.
List existing BigML supervised models with credential-safe pagination metadata and compact status details.
Retrieve compact BigML model metadata and field definitions needed to construct prediction input.
Submit a JSON prediction against an existing BigML model and return the prediction resource for polling.
Retrieve the current status and result of one BigML prediction resource for async polling.
List stored BigML prediction resources with normalized status and credential-safe pagination metadata.
Permanently delete one stored BigML prediction resource.
Connect the Apps your work depends on, and give Leina the context to carry the task forward.
Hand off a task while your team is discussing it. Leina uses your connected tools and brings the result back to the conversation.
See How Leina Works in SlackBoth predictions have finished. The model returned “renew” for Cedar and “not renew” for Brook.
Inspect the existing model first. Supply a JSON object using its field identifiers or supported field names and values appropriate to those fields.
Creation returns a prediction resource with status information. Read that resource again to retrieve its result after processing completes.
These operations use existing models and manage predictions. Model training is not included in this connection.
Start with one task you already need to do. Tell Leina what a finished result should look like.
Connect BigML, choose what to share, and hand off your first task.