t-SNE: Simple Test Case

Example 5: Minimal Example (6 points)

Simple test case with 6 points in 3 obvious groups. Good for testing drag-and-drop and basic algorithm behavior.

Feature Selection for Distance Calculation:

Available Features:

Selected Features:

Rescaling: (Changes which variables determine similarity)

Color nodes by:

Perplexity: 2.0 (5-100, typically 15-50)

Learning Rate: 50.0 (10-1000, typically 100-500)

Convergence threshold:

Max iterations:

Early exaggeration iters:

Exaggeration factor:

Iteration: 0
         
Movement (last iteration): 0.000
Status: Ready

Aspect Ratio: 0.6

Zoom: 1.0x

Tip: Drag nodes to manually reposition. "Run to Convergence" uses early exaggeration for the configured number of iterations; "Step (small)" never uses exaggeration; "Exaggerated Step" always uses it.

Data: minimal_data.csv

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