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AutoML for Bike Rentals Predicting

AutoML for Bike Rentals Predicting
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 isevaluated on the test data.Bike Sharing Data set is available on https://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset Bike SharingDataset (daily)Top : Train + Validation setsBottom : Test setPredictEvaluate ontest dataExecute up-streambefore configuration Table Reader Partitioning Workflow Executor Numeric Scorer AutoML (Regression) 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 isevaluated on the test data.Bike Sharing Data set is available on https://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset Bike SharingDataset (daily)Top : Train + Validation setsBottom : Test setPredictEvaluate ontest dataExecute up-streambefore configuration Table Reader Partitioning Workflow Executor Numeric Scorer AutoML (Regression)

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Created by: paolotamag
Created at: 2020-06-24
On NodePit since: 2021-12-18
Last update: 2024-04-25
Created with KNIME version: v4.5.0
Tags: autoMLautomated machine learningguided analyticsintegrated deploymentregressionnumeric predictions

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