📄️ Introduction to AutoML
AutoML automates simClassify+ model creation for classification data sets, guiding users through a rapid training process.
📄️ Creating a new AutoML Process
Start a new AutoML project or resume an exited one, and how the project name is used to name the resulting models.
📄️ AutoML Navigation Bar
The AutoML Navigation Bar's five stages and how completed, current, and locked steps are indicated.
📄️ Selecting an AutoML Data Set
Choose an existing data set or upload a new one to a folder as the training data source for an AutoML project.
📄️ AutoML Project Information Page
The AutoML Project Information page, which reports the current stage, task, and progress of a running AutoML process.
📄️ Providing AutoML Data Specifications
Select an ID Column and Class Column and review ML Studio's Specification Analyzer results during the AutoML data setup step.
📄️ AutoML Model Optimization
AutoML's Low, Medium, and Exhaustive grid levels control how many hyperparameter combinations the optimizer evaluates.
📄️ AutoML Model Selection
How AutoML's Model Selection page ranks grid experiment results and picks a threshold using the Matthews Correlation Coefficient.
📄️ AutoML Model Creation
The AutoML Model Creation step, where a model trains, moves to Running status, and becomes available to query.