Exercise1

<p><strong>Chapter 4/Exercise 1</strong></p><p>This workflow is an exercise for model training and model evaluation. Based on the <em>wine.csv</em> dataset, this workflow trains a Decision Tree model to predict the wine class. It performs the following steps:</p><ol><li><p><strong>Data access:</strong> Reading wine.csv from the KBLdata folder (<em>CSV Reader</em> node)</p></li><li><p><strong>Data preprocessing:</strong> Converting the "Class" column from integer to string (<em>Number to String</em> node) and then partitions the data into training set (80%) and test set (20%) (<em>Table Partitioner</em> node).</p></li><li><p><strong>Model training:</strong> Training a Decision Tree (<em>Decision Tree Learner</em> node) to predict the wine class based on the other attributes in the dataset. Then, applying the trained model to the test set (<em>Decision Tree Predictor</em> node).</p></li><li><p><strong>Model evaluation:</strong> Comparing predicted class values to original values to understand how good/bad the model is performing.</p></li></ol>