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01 Taxi Demand Prediction on Spark Training

Taxi Demand Prediction on Spark Training

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

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Created by: dewi
Created at: 2019-02-07
On NodePit since: 2021-11-04
Last update: 2024-11-17
Created with KNIME version: v5.2.4
Tags: Demand predictionrandom foresttime series predictionSpark clusterNYC taxi datsetIoTInternet of Things

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