I want to use the DBSCAN clustering algorithm in order to detect outliers in my dataset. As this is an unsupervised learning approach, do I need to split my dataset in training and test data or is testing the DBSCAN algorithm just not possible?
For outlier detection reasons, should I feed the DBSCAN model with my entire dataset?
Aucun commentaire:
Enregistrer un commentaire