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  • 02_Taxi_Demand_Prediction_Training_workflow
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Taxi demand prediction training workflow

Demand prediction Random forest Time series prediction Spark cluster NYC taxi datset
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In this use case, we will use the NYC taxi dataset and a Random Forest to train a simple time series prediction model to predict taxi demand in the next hour based on data from past hours. Given the large size of the dataset, we train and deploy the machine learning model of choice on a Spark cluster. The KNIME Big Data Extension allows you to run a KNIME workflow on the big data platform you prefer, via in-database processing or via Spark.

Used extensions & nodes

Created with KNIME Analytics Platform version 4.1.2
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    KNIME Core Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.2

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    KNIME Data Generation Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

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    KNIME Extension for Apache Spark Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.1

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    KNIME Extension for Local Big Data Environments Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

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    KNIME File Handling Nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.1

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    KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.2

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    KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.2

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