L1 ball: Manhattan distance, L2 ball: Euclidean distance. Diamond shape for L1 reflects Manhattan geometry, circle for L2 reflects Euclidean geometry
Image: Public domain, via Wikimedia Commons
L1 ball: Manhattan distance, L2 ball: Euclidean distance. Diamond shape for L1 reflects Manhattan geometry, circle for L2 reflects Euclidean geometry
the Lp norm ball shape changes as p goes from 1 to 2 to infinity
As p increases from 1 to 2 to infinity, the Lp norm ball becomes more spherical
Chebyshev distance
Chebyshev distance is named after Pafnuty Chebyshev
Norm (mathematics)
L∞ norm equals max absolute value
Distance transform
Manhattan distance formula: |x1 - x2| + |y1 - y2|
L1 vs L2 regularization: L1 gives sparsity (feature selection), L2 gives small weights
L1 regularization: L1 = L2 + sparsity; L2 regularization: L2 = L1 + small weights
Euclidean distance
Euclidean distance formula: √((x2 - x1)² + (y2 - y1)²)
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