This workflow deploys the lean restocking system for bycicles in Washington DC stations, as trained in another workflow. Data is a subset of the bike dataset. The model will predict one of three classes: Add bikes; Remove bikes; No Action. 1. Data are read and prepared as in the training workflow, that is: Bike ratios are calculated as total # bikes/available spots by station; 10 past ratios in input vector 2. Model is read and applied 3. Prediction class (besides No Action) is accepted only if confidence exceeds a given threshold 4. Stations in need of bike reshuffling are shown in a web dashboard
Used extensions & nodes
Created with KNIME Analytics Platform version 4.5.0
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