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Twain_​Companies_​Exploration

Raw dataset from the file into the Knime . Starting point
CSV Reader
Used Seed for UID number
Table Partitioner
Normalize features
Normalizer (PMML)
Provides an overview of the dataset
Data Explorer
Display descriptive statistics
Statistics View
Handles missing values in the data set by applying the selection imputation method
Missing Value
spilt data set into 80 training and 20 testing for model evaluation
Table Partitioner
Normalizize numeric features to ensure consistent scaling
Normalizer
Selected only relevant columns
Column Filter
Trains a random regression model
Random Forest Learner (Regression)
Compute pairwise between observations
Numeric Distances
Coverts numeric values format
Number to String
Selected only the relevant columns for the regressions
Column Filter
Trained a logistic regression model to predict
Logistic Regression Learner
normalize features for DBSAN And Distance Calculation
Normalizer (PMML)
applies the trained random forest
Random Forest Predictor (Regression)
Density base clustering algorithm that identifies cluster and outliers
DBSCAN
evaluated model performance using metrics
Scorer
Selected interest coverage ratio and Net income stockholders
Scatter Plot
Performs K-means cluster to a group similar obersvation
k-Means
Assign colors for easier visualization
Color Manager

Nodes

Extensions

Links

Download

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

Download Workflow
Created by: Franc
Created at: 2026-05-21
On NodePit since: 2026-05-24
Last update: 2026-05-24
Created with KNIME version: v5.11.0

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