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Demand predictionRandom forestTime series predictionSpark clusterNYC taxi datset
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Versionv1.0 KNIME Analytics Platform 5.2.4Latest, created on 
Jun 10, 2024 4:19 PM
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Taxi demand prediction deployment 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.
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Used extensions & nodes

Created with KNIME Analytics Platform version 5.2.4
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    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.2.4

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    KNIME Basic File System ConnectorsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.2.4

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    KNIME Data GenerationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.2.0

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    KNIME Extension for Apache SparkTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.2.4

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    KNIME Extension for Local Big Data EnvironmentsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.2.4

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    KNIME JavasnippetTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.2.0

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    KNIME Quick FormsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.2.4

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    KNIME ViewsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 5.2.4

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