4. Clustering and Regression

<p><strong>Clustering and Regression</strong></p><p>This workflow reads the two datasets (training and test set) created in the workflow "1. Data Preparation" and shows a few more machine learning algorithms:</p><ol><li><p>A linear regression to predict the number of hours/week given all other attribute values (<em>Linear Regression Learner</em> and <em>Regression Predictor</em> nodes).</p></li><li><p>A k-Means clustering to detect patterns in the dataset by grouping together the most similar data rows.</p></li></ol><p>Remember, that k-Means, like Neural Networks, needs normalized data.</p><p>The <em>Statistics </em>node mainly produces general statistical measures about one data column, including a roughly drawn histogram.</p>