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KNIME_​projectSIAD

CSV Reader
distribuição das classes Target (Dropout/Graduate)
Value Counter
Divisão 80% treino / 20% teste
Table Partitioner
aprender com modelo.
Decision Tree Learner
Decision Tree Predictor
Capacidade geral de distinguir as classes
ROC Curve
Row Filter
Capacidade geral de distinguir as classes
ROC Curve
Row Filter
Row Filter
perceber se há missing values
Statistics
5NN
K Nearest Neighbor
Comparação entre métricas dos diferentes modelos
Bar Chart
ROC Curve
Avalia correlação entre cada par de Features
Linear Correlation
ROC Curve
Exclui 1 feature em cada par com correlação acima do Treshold
Correlation Filter
Métricas
Scorer
Guardar nome do modelo
Constant Value Column Appender
Gradient Boosted Trees Learner
Random Forest Predictor
Row Filter
10NN
K Nearest Neighbor
Métricas
Scorer
Métricas
Scorer
Métricas
Scorer
Random Forest Learner
Guardar nome do modelo
Constant Value Column Appender
Gradient Boosted Trees Predictor
Métricas
Scorer
Guardar nome do modelo
Constant Value Column Appender
Row Filter
filtrar apenas graduated and dropout
Row Filter
Juntar os scorers todosna mesma tabela
Concatenate
Normalizer
Guardar nome do modelo
Constant Value Column Appender
Capacidade geral de distinguir as classes
ROC Curve
Guardar nome do modelo
Constant Value Column Appender

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: anari
Created at: 2026-05-07
On NodePit since: 2026-05-20
Last update: 2026-05-20
Created with KNIME version: v5.11.0

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