This workflow demonstrates how to predict the number of rented bikes. Pre-processing, hyper-parameter optimization, and training are done by the AutoML (Regression) component. Similar pre-processing and the best trained model are then applied to the test data via Workflow Executor node. Finally, the model is evaluated on the test data. Bike Sharing Data set is available on https://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset
Used extensions & nodes
Created with KNIME Analytics Platform version 4.5.0
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