Genetic programming and serial processing for time series classification

摘要: This work describes an approach devised by the authors for time series classification. In our genetic programming is used in combination with a serial processing of data, where last output result The use classification, although still field more research needed, not new. However, application to classification tasks normally done considering input data as feature vector. That is, best knowledge, there are examples literature approaches processed serially and considered result. presented here fills gap existing literature. was tested three different problems. Two them real world problems whose were gathered online or conference competitions. As published results these two this gives us chance compare performance against top performing methods. obtained competitive both competitions, showing its potential solving main advantage that it can easily handle very large datasets.