This work describes the results obtained by applying a machine learning method based on cluster analysis applied to a database of data that simulates an industrial production process. The topic is pattern recognition, and the method is compared to other 7 methods from literature: Classification and Regression Trees; C4.5; PART; Bagging CART; Random Forest; Boosted C5.0; Support Vector Machines.
|Titolo:||Experimental findings in machine learning methods development|
|Data di pubblicazione:||2020|
|Appare nelle tipologie:||5.1 Rapporto Tecnico ENEA|