This topic describes how to generate models in Machine Learning Platform for AI by using the logistic regression for binary classification algorithm.

Prerequisites

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

Procedure

  1. Go to a Machine Learning Studio project.
    1. Log on to the PAI console.
    2. In the left-side navigation pane, choose Model Training > Studio-Modeling Visualization.
    3. In the upper-left corner of the page, select the region that you want.
    4. Optional:In the search box on the PAI Visualization Modeling page, enter the name of a project to search for the project.
    5. Find the project that you want and click Machine Learning in the Operation column.
  2. In the left-side navigation pane, click Components.
  3. In the Components pane, choose Machine Learning > Binary Classification. Then, drag the Logistic Regression for Binary Classification component to the canvas and connect it to the components prepared during data visualization. For more information, see Visualize data.
  4. Click the Logistic Regression for Binary Classification component on the canvas. On the Fields Setting tab on the right side, set the Target Columns parameter to ifhealth. In the Training Feature Columns section, select all columns except for ifhealth, as shown in the following figure. Logistic regression for binary classification
  5. Right-click the Logistic Regression for Binary Classification component. In the shortcut 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 Evaluate the model.