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JKI-S3_​challenge14

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.

Brute Force auto arima auto sarima mean train: 2015-2017 test: 2018 select typeoptimized by AICARIMA LearnerARIMA PredictorARIMA Learnerpmdarimaauto arimaacfdecomposed plotpacfauto sarimaCSV Reader GroupBy Row Splitter Parameter OptimizationLoop Start Row Filter ParameterOptimization Loop End Table Rowto Variable String to Date&Time Python Script Table Rowto Variable Python Script Python Script Numeric Scorer Concatenate Line Plot Conda EnvironmentPropagation Python Script Python View Python View Python View Concatenate Line Plot Concatenate Line Plot Python Script Brute Force auto arima auto sarima meantrain: 2015-2017 test: 2018 select typeoptimized by AICARIMA LearnerARIMA PredictorARIMA Learnerpmdarimaauto arimaacfdecomposed plotpacfauto sarimaCSV Reader GroupBy Row Splitter Parameter OptimizationLoop Start Row Filter ParameterOptimization Loop End Table Rowto Variable String to Date&Time Python Script Table Rowto Variable Python Script Python Script Numeric Scorer Concatenate Line Plot Conda EnvironmentPropagation Python Script Python View Python View Python View Concatenate Line Plot Concatenate Line Plot Python Script

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Created by: 00178048
Created at: 2024-08-16
On NodePit since: 2024-08-20
Last update: 2026-01-06
Created with KNIME version: v5.3.1
Tags: JKISeason3-14

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