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NTU FVAS Group Assignment - Hospital Readmission (20260720)

balanced test set (n = 900)
Logistic Regression Predictor
11.67% FNRevaluation metrics <80%
Scorer
CSV Reader
293 rules applied
Decision Tree to Ruleset
Decision Tree Predictor
no pruning
Decision Tree Learner
10-level decision tree
Decision Tree to Image
70/30 train/test split2100/900 random samples
Table Partitioner
Yes = readmission n = 1132
Row Filter
1.5% FNRevaluation metrics >96%
Scorer
CSV Reader
Yes = readmission (random)n = 968
Row Sampler
Balanced train setn = 1936
Concatenate
No = readmissionn = 968
Row Filter
179 rules applied
Decision Tree to Ruleset
CART using test setn = 900
Decision Tree Predictor
no pruning
Decision Tree Learner
11-level decision tree
Decision Tree to Image
reduced to only 3 categories + readmission (reference)
Column Filter
12.89% FNRevaluation metrics <80%
Scorer
reduced to only 4 categories + readmission (reference)
Column Filter
no train/test set
CSV Reader
Reduced to only 5 x-variables
Logistic Regression Learner
Logistic Regression Predictor
11.37% FNRevaluation metrics <80%
Scorer
reduced to only 5 categories + readmission (reference)
Column Filter
CSV Reader
70/30 train/test split2100/900 random samples
Table Partitioner
MDL pruning
Decision Tree Learner
5-level decision tree
Decision Tree to Image
43 rules applied
Decision Tree to Ruleset
Decision Tree Predictor
36 rules applied
Decision Tree to Ruleset
CART using test setn = 900
Decision Tree Predictor
9.57% FNRevaluation metrics >80%
Scorer
CSV Reader
MDL Pruning
Decision Tree Learner
5-level decision tree
Decision Tree to Image
70/30 train/test split2100/900 random samples
Table Partitioner
CSV Reader
Logistic Regression Predictor
Yes = readmission (random)n = 968
Row Sampler
Yes = readmission n = 1132
Row Filter
13.67% FNRevaluation metrics 70-80%
Scorer
70 train / 30 test split set
Table Partitioner
reduced to 4 x-variables
Logistic Regression Learner
Yes = readmissionn = 1140
Row Filter
10.11% FNRevaluation metrics <82%
Scorer
Balanced train setn = 1936
Concatenate
CSV Reader
No = readmissionn = 968
Row Filter
balanced train set n = 1920
Concatenate
reduced to 3 x-variables
Logistic Regression Learner
No = readmissionn = 960
Row Filter
Yes = readmission (random)n = 960
Row Sampler

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Created by: kelvinng
Created at: 2026-07-18
On NodePit since: 2026-07-21
Last update: 2026-07-23
Created with KNIME version: v5.11.0

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