Change detection in classification models induced from time series data Academic Article uri icon

abstract

  • Most classification methods are based on the assumption that the historic data involved in building and verifying the model is the best estimator of what will happen in the future. One important factor that must not be set aside is the time factor. As more data is accumulated into the problem domain, incrementally over time, one must examine whether the new data agrees with the previous datasets and make the relevant assumptions about the future. This work presents a new change detection methodology, with a set of statistical estimators …

publication date

  • January 1, 2004