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Welcome to Naive Bayes Visualizer
Explore how the Gaussian Naive Bayes classifier works through interactive visualization. Click on the canvas to add data points, train the model, and watch decision boundaries form in real time.
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Adding Data Points
Select a class from the class selector, then click anywhere on the canvas to place a data point. Each class is shown in a different color. Add at least 2 points per class to begin training.
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Training the Model
Click "Train Model" to compute class priors and Gaussian distributions for each feature. The decision boundary and probability heatmap will be rendered on the canvas.
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Understanding the Output
The decision boundary shows where the classifier changes its prediction. The probability panel shows posterior probabilities as you hover over the canvas. The stats panel shows learned parameters.