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MAN7091

Excel Reader
Create derived features Age and TotalChildren
Expression
Train random forest regression model to predict Revenue
Random Forest Learner (Regression)
Overall statistics and distributions
Statistics
Correlation analysis of numeric columns
Linear Correlation
Create age groups
Binner
Aggregate revenue by education and marital status
GroupBy
Top customers by revenue
Top k Row Filter
Predict Revenue on test data with random forest regression
Random Forest Predictor (Regression)
Evaluate random forest regression performance
Numeric Scorer
Aggregate Revenue and Income by Education
GroupBy
Visualize mean Revenue by Education
Bar Chart
Visualize aggregated revenue and income by education and marital status
Bar Chart
Handle missing values before grouped bar chart
Missing Value
Numeric Scorer
Replace missing values correctly before downstream analysis and modeling
Missing Value
Box Plot
Predict on test set
Decision Tree Predictor
Split data into train and test
Table Partitioner
Normalize numeric variables for clustering
Normalizer
Train decision tree model
Decision Tree Learner
Cluster customers into segments
Fuzzy c-Means
Evaluate classification predictions
Scorer
Select numeric and key demographic columns for customer segmentation and regression
Column Filter
Predict Revenue on test data with linear regression
Regression Predictor
Evaluate linear regression performance
Numeric Scorer
Evaluate clustering quality with silhouette coefficient
Silhouette Coefficient
Train linear regression model to predict Revenue
Linear Regression Learner

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Created by: user
Created at: 2026-06-05
On NodePit since: 2026-06-06
Last update: 2026-06-09
Created with KNIME version: v5.11.0

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