In this topic, the logistic regression for binary classification algorithm is used as an example to describe how to generate models in Machine Learning Platform for AI.

Prerequisites

Data visualization is complete. For more information, see Data visualization.

Procedure

  1. Log on to the Machine Learning Platform for AI console.
  2. In the left-side navigation pane, choose Model Training > Studio-Modeling Visualization, and navigate to the PAI Visualization Modeling page.
  3. Click Machine Learning.Machine learning
  4. In the left-side navigation pane, click Components.
  5. In the Components list, choose Machine Learning > Binary Classification. Then, drag and drop the Logistic Regression for Binary Classification component onto the canvas, and connect it to the components prepared during Data visualization.
  6. Click the Logistic Regression for Binary Classification component on the canvas. On the uicontrol Fields Setting tab on the right side, set Target Columns to ifhealth. In the Training Feature Columns section, select all columns except for the Target Columns, as shown in the following figure. Logistic regression for binary classification
  7. Right-click the Logistic Regression for Binary Classification component. In the menu that appears, click Run This Node.

What to do next

After algorithm modeling is complete. You can evaluate the model. For more information, see Model evaluation.