Read the wine.csv dataset.
Train a Logistic Regression Model to predict whether a wine is red or white.
- Use the Normalizer(PMML) node to z normalize all numerical columns.
- Partition the dataset into a training set (80%) and a test set (20%) using the Partitioning node
with the stratified sampling option on the column “Income”.
- Use the Logistic Regression Learner Node to train the model on the training set and the Logistic
Regression Predictor Node to apply the model to the test set.
- Use the Scorer node to evaluate the accuracy of the model.
Workflow
Question3
Used extensions & nodes
Created with KNIME Analytics Platform version 4.1.1
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