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Knime_​ProjectV2

Alunos com estatudo "Enrolled", ou seja, que não podem ser usados para treinar o modelo ainda.

K-NN analysis

Logistic Regression analysis

Decision Tree analysis

Random Forest Analysis

Gradient Boosted Trees analysis

Bar Chart
ROC Curve
Scorer
Scorer
ROC Curve
Random Forest Learner
Random Forest Predictor
Random Forest Learner
Linear Correlation
Random Forest Predictor
X-Partitioner
Parameter Optimization Loop Start
para ver o número exato de variáveis que devem ser removidas (se faz sentido face ao removido manualmente com o heatmap)
Correlation Filter
variáveis retiradas manualmente, considerando o heatmap debaixo
Column Filter
Para avaliar as correlações entre variáveis
Heatmap
Scorer
Parameter Optimization Loop End
X-Aggregator
Table Partitioner
Gradient Boosted Trees Learner
ROC Curve
Gradient Boosted Trees Predictor
Table Row to Variable
Normalizer
Table Partitioner
Scorer
X-Partitioner
X-Aggregator
Table Row to Variable
Scorer
Parameter Optimization Loop End
ROC Curve
Parameter Optimization Loop Start
K Nearest Neighbor
X-Partitioner
CSV Reader
remover o dado "enrolled" da tabela
Nominal Value Row Filter
onde está o "enrolled"
Nominal Value Row Filter
70/30 split
Table Partitioner
Decision Tree Learner
Decision Tree Predictor
Gradient Boosted Trees Predictor
X-Aggregator
Parameter Optimization Loop Start
Gradient Boosted Trees Learner
Logistic Regression Predictor
Table Row to Variable
ROC Curve
Table Partitioner
Scorer
Logistic Regression Learner
Parameter Optimization Loop End
Parameter Optimization Loop Start
Logistic Regression Learner
Scorer
X-Partitioner
Logistic Regression Predictor
X-Aggregator
Scorer
Parameter Optimization Loop End
Parameter Optimization Loop Start
Parameter Optimization Loop End
Table Row to Variable
"Scorer" para decision tree
Scorer
Table Row to Variable
K Nearest Neighbor
Decision Tree Learner
X-Partitioner
X-Aggregator
Domain Calculator
Decision Tree Predictor
Scorer

Nodes

Extensions

Links