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Multivariate_​Time_​Series_​Predictions

This is a simple example workflow for multivariant time series analysis using Keras.

Define network Preprocessing Train network Preprocessing Read london_merged.csvfrom kaggleInput shape: 10,1310 steps13 dimensions per step100 unitsReLU with 1 unitNode 14850 % validation50% testingNode 151Node 152Node 156Node 158Node 15980 % training20% test+validationDay of monthDay of weekMonth HourNode 188 File Reader Keras Input Layer Keras LSTM Layer Keras Dense Layer Keras NetworkLearner Partitioning Keras NetworkExecutor Numeric Scorer Normalizer Denormalizer Column Appender Line Plot (Plotly) Partitioning Normalizer (Apply) Extract Date Fields PreprocessingTrainingset Preprocessing Testand Validation Set Extract and DenomrmalizePredictions Define network Preprocessing Train network Preprocessing Read london_merged.csvfrom kaggleInput shape: 10,1310 steps13 dimensions per step100 unitsReLU with 1 unitNode 14850 % validation50% testingNode 151Node 152Node 156Node 158Node 15980 % training20% test+validationDay of monthDay of weekMonth HourNode 188File Reader Keras Input Layer Keras LSTM Layer Keras Dense Layer Keras NetworkLearner Partitioning Keras NetworkExecutor Numeric Scorer Normalizer Denormalizer Column Appender Line Plot (Plotly) Partitioning Normalizer (Apply) Extract Date Fields PreprocessingTrainingset Preprocessing Testand Validation Set Extract and DenomrmalizePredictions

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: kathrinmelcher
Created at: 2020-10-13
On NodePit since: 2020-12-17
Last update: 2024-04-27
Created with KNIME version: v4.2.2

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