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Questions3

Questions3 Homework2 Berkant Güneş

Questions3 Homework2 Berkant Güneş

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.

reading wine.csvnormalize dataz - score training set (80%) and a test set (20%)traintestNode 6 File Reader Normalizer (PMML) Partitioning LogisticRegression Learner Logistic RegressionPredictor Scorer reading wine.csvnormalize dataz - score training set (80%) and a test set (20%)traintestNode 6File Reader Normalizer (PMML) Partitioning LogisticRegression Learner Logistic RegressionPredictor Scorer

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Created by: Berkant
Created at: 2020-04-23
On NodePit since: 2020-04-26
Last update: 2024-04-15
Created with KNIME version: v4.1.2

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