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Cancer_​Prediction

Input Dataset
CSV Reader
Remove unnecessary columns
Column Filter
Calculates the scaling parameters only from the Training data and applies the scaling transformation to the Training Set.
Normalizer
Separates the dataset into two independent parts: the Training Set and the Test Set. (80:20)
Table Partitioner
Trains the Machine Learning model using the preprocessed (scaled) Training Set.
Decision Tree Learner
Uses the trained model (from the Learner) to generate predictions on the scaled Test Set.
Decision Tree Predictor
Pie Chart
Decision Tree to Image
Scorer
Measures the model's performance (comparing predictions to actual values) and outputs evaluation metrics
Scorer
Logistic Regression Learner
Random Forest Learner
Visually checks statistical summaries for each column, including mean, min, max, standard deviation, and critically, the count of Missing Values.
Statistics View
Random Forest Predictor
Applies the scaling parameters calculated from the Training Set to the Test Set
Normalizer (Apply)
Logistic Regression Predictor
Scorer

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: dyahalmira
Created at: 2025-11-20
On NodePit since: 2025-11-21
Last update: 2025-11-21
Created with KNIME version: v5.8.0

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