Fault diagnosis is determining which

2. Predictive Model

DM tasks can be conducted through prediction and description models] In general, the prediction models are constructed through the learning of known data classes, whereas the description models arise from the findings obtained in a dataset. In this regard, predictive DM techniques are the straightforward option to perform the diagnosis of equipment and systems since their different operating conditions can be learned and determined by a prediction model. In this model its learning is carried out by means of the analysis of a data training set (input data with known outputs) and then used to predict the unknown output (class or value) of new input data. According to the nature of data (discrete or continuous), the prediction model can be used to perform either classification or regression functionalities] A classification procedure consists of the assignment of an object (unknown class) into one of several predefined classes (predicted class) according to its properties or features. In a different way, a regression procedure involves the modeling of continuous functions to determine new numerical values (predicted values) according to specific inputs. Classification and regression techniques used for fault detection in electric equipment and systems are presented in the following sections.