Machine Learning Pipeline Execution
STAGE 1 RAW DATA SOURCES AUGMENTATION EXPANSION STAGE 2 FEATURE CONSTRUCT STAGE 3 GEOMETRIC TRANSFORM STAGE 4 DISTANCE / DECISION STAGE 5 PREDICTION COPY +JIT W·x TEXT TOKENS "a" "b" "c" POINT CLOUD DIGIT GRID AUGMENT [ +NOISE / JITTER ] N-GRAM TILES a-b b-c c-d TOKEN COUNTERS EXTRACTED VARS v = [ 1.2, 0.0, 3.4, 0.8 ] MATRIX CLAMP z = min(max(Wv + b, -1), 1) WARPED GRID e₁ e₂ W·e MEASURING TAPE VOTE TALLY [7 vs 2] PREDICTION CLASS: ALPHA
STAGE 1: RAW INPUT DATA Hover or Click any stage node to inspect logic
Pipeline active. Data tokens and spatial measurements flow left-to-right through extraction, spatial transformation, and neighborhood scoring.
pipeline.execute(input_stream)