Maximum Likelihood Estimate:

Decision Boundary between two Gaussians

Alternative visualization

This interactive visualization is designed to help you gain a visual understanding of how two-class distributions influence the decision border in a Gaussian classification framework.

Use sliders to modify :

  • The mean (μ) of each class - moves the center of the distributions
  • The variance (σ²) - controls dispersion around the mean

What can we observe?

  • On the left : a 2D visualization of the two classes
  • On the right : a lateral view

Select a SIMPLE or ADVANCED mode, then experiment with the sliders to observe:

  • how the shape and position of the distributions change,
  • and how they affect the decision boundary.

Introduction & Visualization