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Solution3

Solution 3

Solution 3

• 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.

accuracy80% for training set20% for testing settrain modelz - score normalizationprediction modelread wine.csvScorer Partitioning LogisticRegression Learner Normalizer (PMML) Logistic RegressionPredictor File Reader accuracy80% for training set20% for testing settrain modelz - score normalizationprediction modelread wine.csvScorer Partitioning LogisticRegression Learner Normalizer (PMML) Logistic RegressionPredictor File Reader

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