3D Naive Bayes Viz

A classifier that learns by shaping 3D probability clouds. It assumes dimensions (Weight, Sweetness, Color) are independent.

Back to Core

Status

Waiting to Learn

Legend

Apple Class

Orange Class

Mystery Fruit

Input Features

W:0.0 S:0.0 C:0.0

Left-Click Rotate | Right-Click Pan | Shift+Drag Lift Y-Axis

Prediction Engine

Apple Likelihood 50%

Prior(.5) × L(0)

Orange Likelihood 50%

Prior(.5) × L(0)

Final Classification

NEUTRAL

⚡ System Logs

> System initialized.

> Waiting for training data...

Control Panel

Search Variance (Alpha) 1.00

Higher alpha = wider probability clouds (High Bias). Lower alpha = tighter clouds (High Variance).

Data Scenario

Switching scenarios resets the robot's memory.

How it works

The robot calculates the center (mean) and spread (variance) of the points it sees.

To predict the mystery fruit, it measures the distance to each cloud center relative to the cloud's size.

Naive Assumption: It processes Width, Sweetness, and Color completely separately, then multiplies the results.