Lorentzian Classification
K-Nearest Neighbors classifier using Lorentzian distance metric instead of Euclidean. Adapts to the non-normal distribution of financial returns.
Why AlgoZilla Uses Lorentzian Classification
Lorentzian distance is better suited for fat-tailed distributions common in crypto. 6 parameter presets generate signal, confidence, z-distance, and mean-distance features.
Feature Variants
AlgoZilla expands every base indicator into multiple variants: raw values, delta (rate of change over 8/12/24 bars), divergences, and multi-timeframe computations across 2H, 4H, 8H, 12H, and 24H horizons. This is what sets AlgoZilla apart: 170+ features, each retrained every two weeks per coin.
Variants: 5 variants
Part of a Bigger Picture
No single indicator drives AlgoZilla decisions. This is one of 170+ features feeding into a machine learning ensemble, retrained every two weeks per coin. The model learns which features matter in each market regime.
