JKISeason3-14_​tark

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Level: Medium

Description: You are a data scientist asked to analyze an avocado dataset by your team. The task at hand is to pick a specific avocado type in the whole of the US and forecast its daily average prices. To do that, you should train, apply, and score an ARIMA model. Do you see any seasonality in the line plot or autocorrelation plots? Do you think a seasonal ARIMA (SARIMA) would perform better? For your model, visualize forecasts and compute scoring metrics.

Authors: Roberto Cadili, Swetha Kannan, and Corey Weisinger

Dataset: Avocado Price Data in the KNIME Community Hub

URL: JKISeason3-14 https://www.knime.com/just-knime-it?pk_vid=f1a9625dd14a14c5171698895027e10b
URL: Datasets https://hub.knime.com/alinebessa/spaces/Just%20KNIME%20It!%20Season%203%20-%20Datasets/Challenge%2014%20-%20Dataset~RjB5piqdiFzdNxI-/?pk_vid=2fd5e66690c265931723734484585795
URL: This challenge thread https://forum.knime.com/t/solutions-to-just-knime-it-challenge-14-season-3/82093?pk_vid=2fd5e66690c265931723734501585795

Nodes

• Component Input6 ×
• Component Output6 ×
• Autocorrelation Plot5 ×
• Column Filter5 ×
• Column Rename (Regex)4 ×
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Extensions

• FeatureKNIME Base nodes
• FeatureKNIME Column Expressions (legacy)
• FeatureKNIME JavaScript Views
• FeatureKNIME JavaScript Views (Labs)
• FeatureKNIME Javasnippet
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