Label for Regression Analysis
Regression models are used to predict continuous values. They provide a function that determines a relationship between an independent variable and a dependent variable, allowing you to find trends in your data.
Plainsight supports labeling images using a regression label type that supports a numerical value. In the future, an API will be available to supply data for training a regression model.
Labeled image for a regression model
- 1.Navigate to the "Label Definitions" tab of your dataset
- 2.Type label name in the "Name" field
- 3.Choose Regression from "Type" dropdown
- 4.Click "Save" button
A Regression schema element creates an array of objects with data consisting of a float value.
Once you've defined your Regression label, you can begin annotating your regression data.
You can train a regression model by specifying Regression as the Model Output Type in your SmartML configuration. Check out our walk-through on building your regression model in Plainsight: