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Retail_​Workflow

Handles missing values
Missing Value
Shows final performance summary
Statistics View
Cleans text columns
String Manipulation (Multi Column)
Removes duplicate records
Duplicate Row Filter
Detects numeric outliers
Numeric Outliers
Keeps required columns
Column Filter
Converts date to Date&Time
String to Date&Time
Evaluates model performance
Numeric Scorer
Splits train and test data
Table Partitioner
Sorts data by date
Sorter
Fills remaining missing values
Missing Value
Saves processed data
Excel Writer
Reorders columns
Column Resorter
Reads the CSV dataset
CSV Reader
Exports prediction results
Excel Writer
Displays data summary
Statistics View
Trains the ARIMA model
ARIMA Learner
Predicts future values
ARIMA Predictor

Nodes

Extensions

  • No modules found

Links

Download

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

Download Workflow
Created by: ASMITA
Created at: 2026-07-13
On NodePit since: 2026-07-15
Last update: 2026-07-24
Created with KNIME version: v5.11.0

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